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description Publicationkeyboard_double_arrow_right Article 2020 France, Cyprus, Italy EnglishPublisher:Oxford University Press (OUP) Funded by:EC | IDPfun, EC | chemREPEATEC| IDPfun ,EC| chemREPEATMier, Pablo; Paladin, Lisanna; Tamana, Stella; Petrosian, Sophia; Hajdu-Soltész, Borbála; Urbanek, Annika; Gruca, Aleksandra; Plewczynski, Dariusz; Grynberg, Marcin; Bernadó, Pau; Gáspári, Zoltán; Ouzounis, Christos A.; Promponas, Vasilis J.; Kajava, Andrey V.; Hancock, John M.; Tosatto, Silvio C. E.; Dosztanyi, Zsuzsanna; Andrade-Navarro, Miguel A.; Mier, Pablo; Paladin, Lisanna; Tamana, Stella; Petrosian, Sophia; Hajdu-Soltész, Borbála; Urbanek, Annika; Gruca, Aleksandra; Plewczynski, Dariusz; Grynberg, Marcin; Bernadó, Pau; Gáspári, Zoltán; Ouzounis, Christos A.; Promponas, Vasilis J.; Kajava, Andrey V.; Hancock, John M.; Tosatto, Silvio C. E.; Dosztanyi, Zsuzsanna; Andrade-Navarro, Miguel A.;Abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs. Short abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC7299295Data sources: PubMed CentralArchivio istituzionale della ricerca - Università di Padova; Briefings in BioinformaticsOther literature type . Article . 2020 . 2019 . Peer-reviewedLicense: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 67 citations 67 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC7299295Data sources: PubMed CentralArchivio istituzionale della ricerca - Università di Padova; Briefings in BioinformaticsOther literature type . Article . 2020 . 2019 . Peer-reviewedLicense: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/bib/bbz007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2017 Belgium, France, Belgium EnglishPublisher:Oxford University Press (OUP) Authors: Brysbaert, Guillaume; Lorgouilloux, Kevin; Vranken, Wim F; Lensink, Marc F;Brysbaert, Guillaume; Lorgouilloux, Kevin; Vranken, Wim F; Lensink, Marc F;Motivation Protein function is directly related to amino acid residue composition and the dynamics of these residues. Centrality analyses based on residue interaction networks permit to identify key residues in a protein that are important for its fold or function. Such central residues and their environment constitute suitable targets for mutagenesis experiments. Predicted flexibility and changes in flexibility upon mutation provide valuable additional information for the design of such experiments. Results We combined centrality analyses with DynaMine flexibility predictions in a Cytoscape app called RINspector. The app performs centrality analyses and directly visualizes the results on a graph of predicted residue flexibility. In addition, the effect of mutations on local flexibility can be calculated. info:eu-repo/semantics/published SCOPUS: ar.j
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5860209Data sources: PubMed CentralVrije Universiteit Brussel Research PortalOther literature type . 2018Data sources: Vrije Universiteit Brussel Research PortalHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC5860209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5860209Data sources: PubMed CentralVrije Universiteit Brussel Research PortalOther literature type . 2018Data sources: Vrije Universiteit Brussel Research PortalHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 France EnglishPublisher:Public Library of Science (PLoS) Authors: Ajjolli Nagaraja, Anamya; Fontaine, Nicolas; Delsaut, Mathieu; Charton, Philippe; +4 AuthorsAjjolli Nagaraja, Anamya; Fontaine, Nicolas; Delsaut, Mathieu; Charton, Philippe; Damour, Cedric; Offmann, Bernard; Grondin-Perez, Brigitte; Cadet, Frederic;pmc: PMC6505829
pmid: 31067238
International audience; The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexity of the system. The mathematical modelling of the system using an analytical approach depends on the many parameters of enzymes which rely on tedious and expensive experiments. The artificial neural network (ANN) method has been successively applied in different fields of science to perform complex functions. In this study, ANN models were trained to predict the flux for the upper part of glycolysis as inferred by NADH consumption, using four enzyme concentrations i.e., phosphoglucoisomerase, phosphofructokinase, fructose-bisphosphate-aldolase, triose-phosphate-isomerase. Out of three ANN algorithms, the neuralnet package with two activation functions, "logistic" and "tanh" were implemented. The prediction of the flux was very efficient: RMSE and R2 were 0.847, 0.93 and 0.804, 0.94 respectively for logistic and tanh functions using a cross validation procedure. This study showed that a systemic approach such as ANN could be used for accurate prediction of the flux through the metabolic pathway. This could help to save a lot of time and costs, particularly from an industrial perspective. The R-code is available at: https://github.com/DSIMB/ANN-Glycolysis-Flux-Prediction.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6505829Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6505829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 7 citations 7 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6505829Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6505829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France EnglishPublisher:Public Library of Science (PLoS) Funded by:EC | ELIXIR-EXCELERATE, ANR | IFB (ex Renabi-IFB)EC| ELIXIR-EXCELERATE ,ANR| IFB (ex Renabi-IFB)Chennen, Kirsley; Weber, Thomas; Lornage, Xavière; Kress, Arnaud; Böhm, Johann; Thompson, Julie; Laporte, Jocelyn; Poch, Olivier;pmc: PMC7394404
pmid: 32735577
International audience; The diffusion of next-generation sequencing technologies has revolutionized research and diagnosis in the field of rare Mendelian disorders, notably via whole-exome sequencing (WES). However, one of the main issues hampering achievement of a diagnosis via WES analyses is the extended list of variants of unknown significance (VUS), mostly composed of missense variants. Hence, improved solutions are needed to address the challenges of identifying potentially deleterious variants and ranking them in a prioritized short list. We present MISTIC (MISsense deleTeriousness predICtor), a new prediction tool based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids. Our approach also uses training sets with a wide spectrum of variant profiles, including both high-confidence positive (deleterious) and negative (benign) variants. Compared to recent state-of-the-art prediction tools in various benchmark tests and independent evaluation scenarios, MISTIC exhibits the best and most consistent performance, notably with the highest AUC value (> 0.95). Importantly, MISTIC maintains its high performance in the specific case of discriminating deleterious variants from benign variants that are rare or population-specific. In a clinical context, MISTIC drastically reduces the list of VUS (<30%) and significantly improves the ranking of "causative" deleterious variants. Pre-computed MISTIC scores for all possible human missense variants are available at http://lbgi.fr/mistic.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7394404Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 13 citations 13 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7394404Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC7394404&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2017 Netherlands, Netherlands, Italy, United Kingdom, United Kingdom, Netherlands, Netherlands, France, United Kingdom, Spain EnglishPublisher:HAL CCSD Funded by:EC | PhenoMeNalEC| PhenoMeNalvan Rijswijk, M; van Rijswijk, M; Beirnaert, C; Beirnaert, C; Caron, C; Cascante, M; Dominguez, V; Dunn, WB; Ebbels, TMD; Giacomoni, F; Gonzalez-Beltran, A; Hankemeier, T; Haug, K; Haug, K; Izquierdo-Garcia, JL; Jimenez, RC; Jimenez, RC; Jourdan, F; Kale, N; Klapa, MI; Kohlbacher, O; Koort, K; Kultima, K; Le Corguillé, G; Moreno, P; Moschonas, NK; Moschonas, NK; Neumann, S; O'Donovan, C; Reczko, M; Rocca-Serra, P; Rosato, A; Rosato, A; Rosato, A; Salek, RM; Salek, RM; Sansone, S-A; Satagopam, V; Schober, D; Shimmo, R; Spicer, RA; Spicer, RA; Spjuth, O; Spjuth, O; Spjuth, O; Thévenot, EA; Thévenot, EA; Viant, MR; Weber, RJM; Willighagen, EL; Willighagen, EL; Zanetti, G; Steinbeck, C; Steinbeck, C;Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. The meeting was funded by PhenoMeNal, European Commission's Horizon2020 programme, grant agreement number 654241 Sí
HAL - UPEC / UPEM; H... arrow_drop_down Europe PubMed CentralArticle . 2017 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC5627583Data sources: PubMed CentralRecolector de Ciencia Abierta, RECOLECTAArticle . 2017Data sources: Recolector de Ciencia Abierta, RECOLECTAFlore (Florence Research Repository)Article . 2017Data sources: Flore (Florence Research Repository)Oxford University Research Archive; F1000ResearchOther literature type . Article . 2017 . 2018 . Peer-reviewedLicense: CC BYSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositorySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 25 citations 25 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 34visibility views 34 download downloads 65 Powered bymore_vert HAL - UPEC / UPEM; H... arrow_drop_down Europe PubMed CentralArticle . 2017 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC5627583Data sources: PubMed CentralRecolector de Ciencia Abierta, RECOLECTAArticle . 2017Data sources: Recolector de Ciencia Abierta, RECOLECTAFlore (Florence Research Repository)Article . 2017Data sources: Flore (Florence Research Repository)Oxford University Research Archive; F1000ResearchOther literature type . Article . 2017 . 2018 . Peer-reviewedLicense: CC BYSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositorySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.12688/f1000research.12342.1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2019 France EnglishPublisher:Oxford University Press (OUP) Funded by:ANR | MUSEANR| MUSESempéré, Guilhem; Pétel, Adrien; Rouard, Mathieu; Frouin, Julien; Hueber, Yann; De Bellis, Fabien; Larmande, Pierre;pmc: PMC6511067
pmid: 31077313
International audience; Background: The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results: Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions: This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6511067Data sources: PubMed CentralAgritropArticle . 2019Full-Text: http://agritrop.cirad.fr/592427/1/giz051.pdfData sources: AgritropMémoires en Sciences de l'Information et de la Communication; HAL-IRD; Hal-DiderotArticle . 2019License: CC BYFull-Text: https://hal.inrae.fr/hal-02627410/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6511067&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6511067Data sources: PubMed CentralAgritropArticle . 2019Full-Text: http://agritrop.cirad.fr/592427/1/giz051.pdfData sources: AgritropMémoires en Sciences de l'Information et de la Communication; HAL-IRD; Hal-DiderotArticle . 2019License: CC BYFull-Text: https://hal.inrae.fr/hal-02627410/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6511067&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 France EnglishPublisher:Oxford University Press (OUP) Funded by:ANR | SUPER, ANR | CALSIMLAB, ANR | ChromaLightANR| SUPER ,ANR| CALSIMLAB ,ANR| ChromaLightAuthors: Vicedomini, Riccardo; Blachon, Clémence; Oteri, Francesco; Carbone, Alessandra;Vicedomini, Riccardo; Blachon, Clémence; Oteri, Francesco; Carbone, Alessandra;pmc: PMC8262732
pmid: 34023906
Abstract The ever-increasing number of genomic and metagenomic sequences accumulating in our databases requires accurate approaches to explore their content against specific domain targets. MyCLADE is a user-friendly webserver designed for targeted functional profiling of genomic and metagenomic sequences based on a database of a few million probabilistic models of Pfam domains. It uses the MetaCLADE multi-source domain annotation strategy, modelling domains based on multiple probabilistic profiles. MyCLADE takes a list of protein sequences and possibly a target set of domains/clans as input and, for each sequence, it provides a domain architecture built from the targeted domains or from all Pfam domains. It is linked to the Pfam and QuickGO databases in multiple ways for easy retrieval of domain and clan information. E-value, bit-score, domain-dependent probability scores and logos representing the match of the model with the sequence are provided to help the user to assess the quality of each annotation. Availability and implementation: MyCLADE is freely available at http://www.lcqb.upmc.fr/myclade. Graphical Abstract Graphical AbstractMyCLADE is a user-friendly web server designed to annotate domains in protein sequences and assist the user in targeted functional profiling of genomic and metagenomic sequences. It is based on a few million profiles of Pfam domains. It provides multiple links to the Pfam and QuickGO databases, logos and scores to help the user evaluate the quality of the annotation.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8262732Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8262732Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC8262732&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 France EnglishPublisher:BioMed Central Funded by:ANR | IFB (ex Renabi-IFB), ANR | RESETANR| IFB (ex Renabi-IFB) ,ANR| RESETAuthors: Martin, Yannick; Page, Michel; Blanchet, Christophe; de Jong, Hidde;Martin, Yannick; Page, Michel; Blanchet, Christophe; de Jong, Hidde;pmc: PMC6558888
pmid: 31185910
Background Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion. Results We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene. Conclusions The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line. Electronic supplementary material The online version of this article (10.1186/s12859-019-2920-4) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6558888Data sources: PubMed CentralHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6558888Data sources: PubMed CentralHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France EnglishPublisher:HAL CCSD Fotis Psomopoulos; Jacques van Helden; Claudine Médigue; Anastasia Chasapi; Christos A. Ouzounis;As genome sequencing efforts are unveiling the genetic diversity of the biosphere with an unprecedented speed, there is a need to accurately describe the structural and functional properties of groups of extant species whose genomes have been sequenced, as well as their inferred ancestors, at any given taxonomic level of their phylogeny. Elaborate approaches for the reconstruction of ancestral states at the sequence level have been developed, subsequently augmented by methods based on gene content. While these approaches of sequence or gene-content reconstruction have been successfully deployed, there has been less progress on the explicit inference of functional properties of ancestral genomes, in terms of metabolic pathways and other cellular processes. Herein, we describe PathTrace, an efficient algorithm for parsimony-based reconstructions of the evolutionary history of individual metabolic pathways, pivotal representations of key functional modules of cellular function. The algorithm is implemented as a five-step process through which pathways are represented as fuzzy vectors, where each enzyme is associated with a taxonomic conservation value derived from the phylogenetic profile of its protein sequence. The method is evaluated with a selected benchmark set of pathways against collections of genome sequences from key data resources. By deploying a pangenome-driven approach for pathway sets, we demonstrate that the inferred patterns are largely insensitive to noise, as opposed to gene-content reconstruction methods. In addition, the resulting reconstructions are closely correlated with the evolutionary distance of the taxa under study, suggesting that a diligent selection of target pangenomes is essential for maintaining cohesiveness of the method and consistency of the inference, serving as an internal control for an arbitrary selection of queries. The PathTrace method is a first step towards the large-scale analysis of metabolic pathway evolution and our deeper understanding of functional relationships reflected in emerging pangenome collections.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7725326Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7725326Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1099/mgen.0.000429&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2020 Luxembourg, Italy, France, United Kingdom, Italy, France, Germany, Spain EnglishPublisher:Public Library of Science (PLoS) Funded by:EC | ELIXIR-EXCELERATEEC| ELIXIR-EXCELERATEGurwitz, Kim T; Singh Gaur, Prakash; Bellis, Louisa J; Larcombe, Lee; Alloza, Eva; Balint, Balint Laszlo; Botzki, Alexander; Dimec, Jure; Dominguez Del Angel, Victoria; Fernandes, Pedro L; Korpelainen, Eija; Krause, Roland; Kuzak, Mateusz; Le Pera, Loredana; Leskošek, Brane; Lindvall, Jessica M; Marek, Diana; Martinez, Paula A; Muyldermans, Tuur; Nygård, Ståle; Palagi, Patricia M; Peterson, Hedi; Psomopoulos, Fotis; Spiwok, Vojtech; Van Gelder, Celia WG; Via, Allegra; Vidak, Marko; Wibberg, Daniel; Morgan, Sarah L; Rustici, Gabriella;ELIXIR is a pan-European intergovernmental organisation for life science that aims to coordinate bioinformatics resources in a single infrastructure across Europe; bioinformatics training is central to its strategy, which aims to develop a training community that spans all ELIXIR member states. In an evidence-based approach for strengthening bioinformatics training programmes across Europe, the ELIXIR Training Platform, led by the ELIXIR EXCELERATE Quality and Impact Assessment Subtask in collaboration with the ELIXIR Training Coordinators Group, has implemented an assessment strategy to measure quality and impact of its entire training portfolio. Here, we present ELIXIR’s framework for assessing training quality and impact, which includes the following: specifying assessment aims, determining what data to collect in order to address these aims, and our strategy for centralised data collection to allow for ELIXIR-wide analyses. In addition, we present an overview of the ELIXIR training data collected over the past 4 years. We highlight the importance of a coordinated and consistent data collection approach and the relevance of defining specific metrics and answer scales for consortium-wide analyses as well as for comparison of data across iterations of the same course. ELIXIR-EXCELERATE is funded by the European Commission within the Research Infrastructures programme of Horizon 2020, grant agreement number 676559 (https://ec.europa.eu/programmes/horizon2020/en/area/researchinfrastructures). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7377377Data sources: PubMed CentralServeur académique lausannoisArticle . 2020License: CC BYData sources: Serveur académique lausannoisPLoS Computational Biology; Publications at Bielefeld University; Recolector de Ciencia Abierta, RECOLECTA; CNR ExploRAOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYRecolector de Ciencia Abierta, RECOLECTAOther literature type . Article . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCOther literature type . Article . 2020License: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCOpen Repository and Bibliography - LuxembourgArticle . 2020Data sources: Open Repository and Bibliography - Luxembourgadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 125visibility views 125 download downloads 204 Powered bymore_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7377377Data sources: PubMed CentralServeur académique lausannoisArticle . 2020License: CC BYData sources: Serveur académique lausannoisPLoS Computational Biology; Publications at Bielefeld University; Recolector de Ciencia Abierta, RECOLECTA; CNR ExploRAOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYRecolector de Ciencia Abierta, RECOLECTAOther literature type . Article . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCOther literature type . Article . 2020License: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCOpen Repository and Bibliography - LuxembourgArticle . 2020Data sources: Open Repository and Bibliography - Luxembourgadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Article 2020 France, Cyprus, Italy EnglishPublisher:Oxford University Press (OUP) Funded by:EC | IDPfun, EC | chemREPEATEC| IDPfun ,EC| chemREPEATMier, Pablo; Paladin, Lisanna; Tamana, Stella; Petrosian, Sophia; Hajdu-Soltész, Borbála; Urbanek, Annika; Gruca, Aleksandra; Plewczynski, Dariusz; Grynberg, Marcin; Bernadó, Pau; Gáspári, Zoltán; Ouzounis, Christos A.; Promponas, Vasilis J.; Kajava, Andrey V.; Hancock, John M.; Tosatto, Silvio C. E.; Dosztanyi, Zsuzsanna; Andrade-Navarro, Miguel A.; Mier, Pablo; Paladin, Lisanna; Tamana, Stella; Petrosian, Sophia; Hajdu-Soltész, Borbála; Urbanek, Annika; Gruca, Aleksandra; Plewczynski, Dariusz; Grynberg, Marcin; Bernadó, Pau; Gáspári, Zoltán; Ouzounis, Christos A.; Promponas, Vasilis J.; Kajava, Andrey V.; Hancock, John M.; Tosatto, Silvio C. E.; Dosztanyi, Zsuzsanna; Andrade-Navarro, Miguel A.;Abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs. Short abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC7299295Data sources: PubMed CentralArchivio istituzionale della ricerca - Università di Padova; Briefings in BioinformaticsOther literature type . Article . 2020 . 2019 . Peer-reviewedLicense: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 67 citations 67 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC7299295Data sources: PubMed CentralArchivio istituzionale della ricerca - Università di Padova; Briefings in BioinformaticsOther literature type . Article . 2020 . 2019 . Peer-reviewedLicense: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1093/bib/bbz007&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2017 Belgium, France, Belgium EnglishPublisher:Oxford University Press (OUP) Authors: Brysbaert, Guillaume; Lorgouilloux, Kevin; Vranken, Wim F; Lensink, Marc F;Brysbaert, Guillaume; Lorgouilloux, Kevin; Vranken, Wim F; Lensink, Marc F;Motivation Protein function is directly related to amino acid residue composition and the dynamics of these residues. Centrality analyses based on residue interaction networks permit to identify key residues in a protein that are important for its fold or function. Such central residues and their environment constitute suitable targets for mutagenesis experiments. Predicted flexibility and changes in flexibility upon mutation provide valuable additional information for the design of such experiments. Results We combined centrality analyses with DynaMine flexibility predictions in a Cytoscape app called RINspector. The app performs centrality analyses and directly visualizes the results on a graph of predicted residue flexibility. In addition, the effect of mutations on local flexibility can be calculated. info:eu-repo/semantics/published SCOPUS: ar.j
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5860209Data sources: PubMed CentralVrije Universiteit Brussel Research PortalOther literature type . 2018Data sources: Vrije Universiteit Brussel Research PortalHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC5860209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2017Full-Text: http://europepmc.org/articles/PMC5860209Data sources: PubMed CentralVrije Universiteit Brussel Research PortalOther literature type . 2018Data sources: Vrije Universiteit Brussel Research PortalHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2018add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC5860209&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 France EnglishPublisher:Public Library of Science (PLoS) Authors: Ajjolli Nagaraja, Anamya; Fontaine, Nicolas; Delsaut, Mathieu; Charton, Philippe; +4 AuthorsAjjolli Nagaraja, Anamya; Fontaine, Nicolas; Delsaut, Mathieu; Charton, Philippe; Damour, Cedric; Offmann, Bernard; Grondin-Perez, Brigitte; Cadet, Frederic;pmc: PMC6505829
pmid: 31067238
International audience; The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexity of the system. The mathematical modelling of the system using an analytical approach depends on the many parameters of enzymes which rely on tedious and expensive experiments. The artificial neural network (ANN) method has been successively applied in different fields of science to perform complex functions. In this study, ANN models were trained to predict the flux for the upper part of glycolysis as inferred by NADH consumption, using four enzyme concentrations i.e., phosphoglucoisomerase, phosphofructokinase, fructose-bisphosphate-aldolase, triose-phosphate-isomerase. Out of three ANN algorithms, the neuralnet package with two activation functions, "logistic" and "tanh" were implemented. The prediction of the flux was very efficient: RMSE and R2 were 0.847, 0.93 and 0.804, 0.94 respectively for logistic and tanh functions using a cross validation procedure. This study showed that a systemic approach such as ANN could be used for accurate prediction of the flux through the metabolic pathway. This could help to save a lot of time and costs, particularly from an industrial perspective. The R-code is available at: https://github.com/DSIMB/ANN-Glycolysis-Flux-Prediction.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6505829Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 7 citations 7 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6505829Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6505829&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France EnglishPublisher:Public Library of Science (PLoS) Funded by:EC | ELIXIR-EXCELERATE, ANR | IFB (ex Renabi-IFB)EC| ELIXIR-EXCELERATE ,ANR| IFB (ex Renabi-IFB)Chennen, Kirsley; Weber, Thomas; Lornage, Xavière; Kress, Arnaud; Böhm, Johann; Thompson, Julie; Laporte, Jocelyn; Poch, Olivier;pmc: PMC7394404
pmid: 32735577
International audience; The diffusion of next-generation sequencing technologies has revolutionized research and diagnosis in the field of rare Mendelian disorders, notably via whole-exome sequencing (WES). However, one of the main issues hampering achievement of a diagnosis via WES analyses is the extended list of variants of unknown significance (VUS), mostly composed of missense variants. Hence, improved solutions are needed to address the challenges of identifying potentially deleterious variants and ranking them in a prioritized short list. We present MISTIC (MISsense deleTeriousness predICtor), a new prediction tool based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids. Our approach also uses training sets with a wide spectrum of variant profiles, including both high-confidence positive (deleterious) and negative (benign) variants. Compared to recent state-of-the-art prediction tools in various benchmark tests and independent evaluation scenarios, MISTIC exhibits the best and most consistent performance, notably with the highest AUC value (> 0.95). Importantly, MISTIC maintains its high performance in the specific case of discriminating deleterious variants from benign variants that are rare or population-specific. In a clinical context, MISTIC drastically reduces the list of VUS (<30%) and significantly improves the ranking of "causative" deleterious variants. Pre-computed MISTIC scores for all possible human missense variants are available at http://lbgi.fr/mistic.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7394404Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 13 citations 13 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7394404Data sources: PubMed CentralHAL-Inserm; Hal-DiderotArticle . 2020add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC7394404&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2017 Netherlands, Netherlands, Italy, United Kingdom, United Kingdom, Netherlands, Netherlands, France, United Kingdom, Spain EnglishPublisher:HAL CCSD Funded by:EC | PhenoMeNalEC| PhenoMeNalvan Rijswijk, M; van Rijswijk, M; Beirnaert, C; Beirnaert, C; Caron, C; Cascante, M; Dominguez, V; Dunn, WB; Ebbels, TMD; Giacomoni, F; Gonzalez-Beltran, A; Hankemeier, T; Haug, K; Haug, K; Izquierdo-Garcia, JL; Jimenez, RC; Jimenez, RC; Jourdan, F; Kale, N; Klapa, MI; Kohlbacher, O; Koort, K; Kultima, K; Le Corguillé, G; Moreno, P; Moschonas, NK; Moschonas, NK; Neumann, S; O'Donovan, C; Reczko, M; Rocca-Serra, P; Rosato, A; Rosato, A; Rosato, A; Salek, RM; Salek, RM; Sansone, S-A; Satagopam, V; Schober, D; Shimmo, R; Spicer, RA; Spicer, RA; Spjuth, O; Spjuth, O; Spjuth, O; Thévenot, EA; Thévenot, EA; Viant, MR; Weber, RJM; Willighagen, EL; Willighagen, EL; Zanetti, G; Steinbeck, C; Steinbeck, C;Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. The meeting was funded by PhenoMeNal, European Commission's Horizon2020 programme, grant agreement number 654241 Sí
HAL - UPEC / UPEM; H... arrow_drop_down Europe PubMed CentralArticle . 2017 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC5627583Data sources: PubMed CentralRecolector de Ciencia Abierta, RECOLECTAArticle . 2017Data sources: Recolector de Ciencia Abierta, RECOLECTAFlore (Florence Research Repository)Article . 2017Data sources: Flore (Florence Research Repository)Oxford University Research Archive; F1000ResearchOther literature type . Article . 2017 . 2018 . Peer-reviewedLicense: CC BYSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositorySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.12688/f1000research.12342.1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 25 citations 25 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 34visibility views 34 download downloads 65 Powered bymore_vert HAL - UPEC / UPEM; H... arrow_drop_down Europe PubMed CentralArticle . 2017 . Peer-reviewedFull-Text: http://europepmc.org/articles/PMC5627583Data sources: PubMed CentralRecolector de Ciencia Abierta, RECOLECTAArticle . 2017Data sources: Recolector de Ciencia Abierta, RECOLECTAFlore (Florence Research Repository)Article . 2017Data sources: Flore (Florence Research Repository)Oxford University Research Archive; F1000ResearchOther literature type . Article . 2017 . 2018 . Peer-reviewedLicense: CC BYSpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital RepositorySpiral - Imperial College Digital RepositoryArticle . 2017Data sources: Spiral - Imperial College Digital Repositoryadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.12688/f1000research.12342.1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2019 France EnglishPublisher:Oxford University Press (OUP) Funded by:ANR | MUSEANR| MUSESempéré, Guilhem; Pétel, Adrien; Rouard, Mathieu; Frouin, Julien; Hueber, Yann; De Bellis, Fabien; Larmande, Pierre;pmc: PMC6511067
pmid: 31077313
International audience; Background: The study of genetic variations is the basis of many research domains in biology. From genome structure to population dynamics, many applications involve the use of genetic variants. The advent of next-generation sequencing technologies led to such a flood of data that the daily work of scientists is often more focused on data management than data analysis. This mass of genotyping data poses several computational challenges in terms of storage, search, sharing, analysis, and visualization. While existing tools try to solve these challenges, few of them offer a comprehensive and scalable solution. Results: Gigwa v2 is an easy-to-use, species-agnostic web application for managing and exploring high-density genotyping data. It can handle multiple databases and may be installed on a local computer or deployed as an online data portal. It supports various standard import and export formats, provides advanced filtering options, and offers means to visualize density charts or push selected data into various stand-alone or online tools. It implements 2 standard RESTful application programming interfaces, GA4GH, which is health-oriented, and BrAPI, which is breeding-oriented, thus offering wide possibilities of interaction with third-party applications. The project home page provides a list of live instances allowing users to test the system on public data (or reasonably sized user-provided data). Conclusions: This new version of Gigwa provides a more intuitive and more powerful way to explore large amounts of genotyping data by offering a scalable solution to search for genotype patterns, functional annotations, or more complex filtering. Furthermore, its user-friendliness and interoperability make it widely accessible to the life science community.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6511067Data sources: PubMed CentralAgritropArticle . 2019Full-Text: http://agritrop.cirad.fr/592427/1/giz051.pdfData sources: AgritropMémoires en Sciences de l'Information et de la Communication; HAL-IRD; Hal-DiderotArticle . 2019License: CC BYFull-Text: https://hal.inrae.fr/hal-02627410/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6511067&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6511067Data sources: PubMed CentralAgritropArticle . 2019Full-Text: http://agritrop.cirad.fr/592427/1/giz051.pdfData sources: AgritropMémoires en Sciences de l'Information et de la Communication; HAL-IRD; Hal-DiderotArticle . 2019License: CC BYFull-Text: https://hal.inrae.fr/hal-02627410/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6511067&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 France EnglishPublisher:Oxford University Press (OUP) Funded by:ANR | SUPER, ANR | CALSIMLAB, ANR | ChromaLightANR| SUPER ,ANR| CALSIMLAB ,ANR| ChromaLightAuthors: Vicedomini, Riccardo; Blachon, Clémence; Oteri, Francesco; Carbone, Alessandra;Vicedomini, Riccardo; Blachon, Clémence; Oteri, Francesco; Carbone, Alessandra;pmc: PMC8262732
pmid: 34023906
Abstract The ever-increasing number of genomic and metagenomic sequences accumulating in our databases requires accurate approaches to explore their content against specific domain targets. MyCLADE is a user-friendly webserver designed for targeted functional profiling of genomic and metagenomic sequences based on a database of a few million probabilistic models of Pfam domains. It uses the MetaCLADE multi-source domain annotation strategy, modelling domains based on multiple probabilistic profiles. MyCLADE takes a list of protein sequences and possibly a target set of domains/clans as input and, for each sequence, it provides a domain architecture built from the targeted domains or from all Pfam domains. It is linked to the Pfam and QuickGO databases in multiple ways for easy retrieval of domain and clan information. E-value, bit-score, domain-dependent probability scores and logos representing the match of the model with the sequence are provided to help the user to assess the quality of each annotation. Availability and implementation: MyCLADE is freely available at http://www.lcqb.upmc.fr/myclade. Graphical Abstract Graphical AbstractMyCLADE is a user-friendly web server designed to annotate domains in protein sequences and assist the user in targeted functional profiling of genomic and metagenomic sequences. It is based on a few million profiles of Pfam domains. It provides multiple links to the Pfam and QuickGO databases, logos and scores to help the user evaluate the quality of the annotation.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8262732Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC8262732&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8262732Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC8262732&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2019 France EnglishPublisher:BioMed Central Funded by:ANR | IFB (ex Renabi-IFB), ANR | RESETANR| IFB (ex Renabi-IFB) ,ANR| RESETAuthors: Martin, Yannick; Page, Michel; Blanchet, Christophe; de Jong, Hidde;Martin, Yannick; Page, Michel; Blanchet, Christophe; de Jong, Hidde;pmc: PMC6558888
pmid: 31185910
Background Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion. Results We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene. Conclusions The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line. Electronic supplementary material The online version of this article (10.1186/s12859-019-2920-4) contains supplementary material, which is available to authorized users.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6558888Data sources: PubMed CentralHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6558888&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2019Full-Text: http://europepmc.org/articles/PMC6558888Data sources: PubMed CentralHAL - UPEC / UPEM; HAL-Pasteur; HAL-Inserm; Hal-DiderotArticle . 2019add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=PMC6558888&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France EnglishPublisher:HAL CCSD Fotis Psomopoulos; Jacques van Helden; Claudine Médigue; Anastasia Chasapi; Christos A. Ouzounis;As genome sequencing efforts are unveiling the genetic diversity of the biosphere with an unprecedented speed, there is a need to accurately describe the structural and functional properties of groups of extant species whose genomes have been sequenced, as well as their inferred ancestors, at any given taxonomic level of their phylogeny. Elaborate approaches for the reconstruction of ancestral states at the sequence level have been developed, subsequently augmented by methods based on gene content. While these approaches of sequence or gene-content reconstruction have been successfully deployed, there has been less progress on the explicit inference of functional properties of ancestral genomes, in terms of metabolic pathways and other cellular processes. Herein, we describe PathTrace, an efficient algorithm for parsimony-based reconstructions of the evolutionary history of individual metabolic pathways, pivotal representations of key functional modules of cellular function. The algorithm is implemented as a five-step process through which pathways are represented as fuzzy vectors, where each enzyme is associated with a taxonomic conservation value derived from the phylogenetic profile of its protein sequence. The method is evaluated with a selected benchmark set of pathways against collections of genome sequences from key data resources. By deploying a pangenome-driven approach for pathway sets, we demonstrate that the inferred patterns are largely insensitive to noise, as opposed to gene-content reconstruction methods. In addition, the resulting reconstructions are closely correlated with the evolutionary distance of the taxa under study, suggesting that a diligent selection of target pangenomes is essential for maintaining cohesiveness of the method and consistency of the inference, serving as an internal control for an arbitrary selection of queries. The PathTrace method is a first step towards the large-scale analysis of metabolic pathway evolution and our deeper understanding of functional relationships reflected in emerging pangenome collections.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7725326Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1099/mgen.0.000429&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7725326Data sources: PubMed Centraladd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1099/mgen.0.000429&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2020 Luxembourg, Italy, France, United Kingdom, Italy, France, Germany, Spain EnglishPublisher:Public Library of Science (PLoS) Funded by:EC | ELIXIR-EXCELERATEEC| ELIXIR-EXCELERATEGurwitz, Kim T; Singh Gaur, Prakash; Bellis, Louisa J; Larcombe, Lee; Alloza, Eva; Balint, Balint Laszlo; Botzki, Alexander; Dimec, Jure; Dominguez Del Angel, Victoria; Fernandes, Pedro L; Korpelainen, Eija; Krause, Roland; Kuzak, Mateusz; Le Pera, Loredana; Leskošek, Brane; Lindvall, Jessica M; Marek, Diana; Martinez, Paula A; Muyldermans, Tuur; Nygård, Ståle; Palagi, Patricia M; Peterson, Hedi; Psomopoulos, Fotis; Spiwok, Vojtech; Van Gelder, Celia WG; Via, Allegra; Vidak, Marko; Wibberg, Daniel; Morgan, Sarah L; Rustici, Gabriella;ELIXIR is a pan-European intergovernmental organisation for life science that aims to coordinate bioinformatics resources in a single infrastructure across Europe; bioinformatics training is central to its strategy, which aims to develop a training community that spans all ELIXIR member states. In an evidence-based approach for strengthening bioinformatics training programmes across Europe, the ELIXIR Training Platform, led by the ELIXIR EXCELERATE Quality and Impact Assessment Subtask in collaboration with the ELIXIR Training Coordinators Group, has implemented an assessment strategy to measure quality and impact of its entire training portfolio. Here, we present ELIXIR’s framework for assessing training quality and impact, which includes the following: specifying assessment aims, determining what data to collect in order to address these aims, and our strategy for centralised data collection to allow for ELIXIR-wide analyses. In addition, we present an overview of the ELIXIR training data collected over the past 4 years. We highlight the importance of a coordinated and consistent data collection approach and the relevance of defining specific metrics and answer scales for consortium-wide analyses as well as for comparison of data across iterations of the same course. ELIXIR-EXCELERATE is funded by the European Commission within the Research Infrastructures programme of Horizon 2020, grant agreement number 676559 (https://ec.europa.eu/programmes/horizon2020/en/area/researchinfrastructures). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7377377Data sources: PubMed CentralServeur académique lausannoisArticle . 2020License: CC BYData sources: Serveur académique lausannoisPLoS Computational Biology; Publications at Bielefeld University; Recolector de Ciencia Abierta, RECOLECTA; CNR ExploRAOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYRecolector de Ciencia Abierta, RECOLECTAOther literature type . Article . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCOther literature type . Article . 2020License: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCOpen Repository and Bibliography - LuxembourgArticle . 2020Data sources: Open Repository and Bibliography - Luxembourgadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pcbi.1007976&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!visibility 125visibility views 125 download downloads 204 Powered bymore_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7377377Data sources: PubMed CentralServeur académique lausannoisArticle . 2020License: CC BYData sources: Serveur académique lausannoisPLoS Computational Biology; Publications at Bielefeld University; Recolector de Ciencia Abierta, RECOLECTA; CNR ExploRAOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYRecolector de Ciencia Abierta, RECOLECTAOther literature type . Article . 2020License: CC BYData sources: Recolector de Ciencia Abierta, RECOLECTAUPCommons. Portal del coneixement obert de la UPCOther literature type . Article . 2020License: CC BYData sources: UPCommons. Portal del coneixement obert de la UPCOpen Repository and Bibliography - LuxembourgArticle . 2020Data sources: Open Repository and Bibliography - Luxembourgadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pcbi.1007976&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu