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description Publicationkeyboard_double_arrow_right Article 2023 SwitzerlandPublisher:MDPI AG Funded by:EC | CY-BIOBANKEC| CY-BIOBANKAuthors: Vasileios L. Zogopoulos; Apostolos Malatras; Konstantinos Kyriakidis; Chrysanthi Charalampous; +10 AuthorsVasileios L. Zogopoulos; Apostolos Malatras; Konstantinos Kyriakidis; Chrysanthi Charalampous; Evanthia A. Makrygianni; Stéphanie Duguez; Marianna A. Koutsi; Marialena Pouliou; Christos Vasileiou; William J. Duddy; Marios Agelopoulos; George P. Chrousos; Vassiliki A. Iconomidou; Ioannis Michalopoulos;handle: 20.500.11850/599339
Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint. ISSN:2073-4409 Cells, 12 (3)
Cells arrow_drop_down CellsOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-4409/12/3/388/pdfadd 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=10.3390/cells12030388&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 Cells arrow_drop_down CellsOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-4409/12/3/388/pdfadd 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=10.3390/cells12030388&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Serbia, Belgium, France, France, Italy, Denmark, Italy, FrancePublisher:Oxford University Press (OUP) Funded by:MESTD | Ministry of Education, Sc..., EC | SMILE, NIH | Gene Ontology Consortium +3 projectsMESTD| Ministry of Education, Science and Technological Development, Republic of Serbia, Grant no. 451-03-68/2020-14/200017 (University of Belgrade, Institute of Nuclear Sciences 'Vinca', Belgrade-Vinca) ,EC| SMILE ,NIH| Gene Ontology Consortium ,EC| IDPfun ,EC| MIMIC ,EC| PhasAGEFederica Quaglia; Bálint Mészáros; Edoardo Salladini; András Hatos; Rita Pancsa; Lucía B. Chemes; Mátyás Pajkos; Tamas Lazar; Samuel Peña-Díaz; Jaime Santos; Veronika Ács; Nazanin Farahi; Erzsébet Fichó; Maria Cristina Aspromonte; Claudio Bassot; Anastasia Chasapi; Norman E. Davey; Radoslav Davidovic; László Dobson; Arne Elofsson; Gábor Erdős; Pascale Gaudet; Michelle G. Giglio; Juliana Glavina; Javier Iserte; Valentin Iglesias; Zsofia E. Kalman; Matteo Lambrughi; Emanuela Leonardi; Sonia Longhi; Sandra Macedo-Ribeiro; Emiliano Maiani; Julia Marchetti; Cristina Marino-Buslje; Attila Mészáros; Alexander Miguel Monzon; Giovanni Minervini; Suvarna Nadendla; Juliet F Nilsson; Marian Novotný; Christos A. Ouzounis; Nicolas Palopoli; Elena Papaleo; Pedro Pereira; Gabriele Pozzati; Vasilis J. Promponas; Jordi Pujols; Alma Carolina Sanchez Rocha; Martín N. Salas; Luciana Rodriguez Sawicki; Eva Schad; Aditi Shenoy; Tamás Szaniszló; Konstantinos D. Tsirigos; Nevena Veljkovic; Gustavo Parisi; Salvador Ventura; Zsuzsanna Dosztányi; Peter Tompa; Silvio C. E. Tosatto; Damiano Piovesan;The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
Archivio Istituziona... arrow_drop_down Archivio Istituzionale (AperTO); Nucleic Acids Research; Archivio istituzionale della ricerca - Università di Padova; Vrije Universiteit Brussel Research PortalOther literature type . Article . 2022 . 2021 . Peer-reviewedLicense: CC BYEurope PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8728214Data sources: PubMed CentralOnline Research Database In TechnologyArticle . 2022Data sources: Online Research Database In TechnologyHAL Descartes; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2022License: CC BY NCFull-Text: https://hal.science/hal-03463975/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=10.1093/nar/gkab1082&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 100 citations 100 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!visibility 71visibility views 71 download downloads 76 Powered bymore_vert Archivio Istituziona... arrow_drop_down Archivio Istituzionale (AperTO); Nucleic Acids Research; Archivio istituzionale della ricerca - Università di Padova; Vrije Universiteit Brussel Research PortalOther literature type . Article . 2022 . 2021 . Peer-reviewedLicense: CC BYEurope PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8728214Data sources: PubMed CentralOnline Research Database In TechnologyArticle . 2022Data sources: Online Research Database In TechnologyHAL Descartes; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2022License: CC BY NCFull-Text: https://hal.science/hal-03463975/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=10.1093/nar/gkab1082&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Czech RepublicPublisher:Oxford University Press (OUP) Funded by:EC | OBERON, EC | HBM4EUEC| OBERON ,EC| HBM4EUFlorence Jornod; Thomas Jaylet; Ludek Blaha; Denis Sarigiannis; Luc Tamisier; Karine Audouze;Abstract Motivation Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome. Results Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment. Availability and implementation AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8796376Data sources: PubMed CentralUniverzitní repozitář Masarykovy univerzityArticle . 2022Data sources: Univerzitní repozitář Masarykovy univerzityadd 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/bioinformatics/btab750&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 25 citations 25 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8796376Data sources: PubMed CentralUniverzitní repozitář Masarykovy univerzityArticle . 2022Data sources: Univerzitní repozitář Masarykovy univerzityadd 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/bioinformatics/btab750&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021Publisher:MDPI AG Spyros Tastsoglou; Marios Miliotis; Ioannis Kavakiotis; Athanasios Alexiou; Eleni C. Gkotsi; Anastasia Lambropoulou; Vasileios Lygnos; Vasiliki Kotsira; Vasileios Maroulis; Dimitrios Zisis; Giorgos Skoufos; Artemis G. Hatzigeorgiou;Simple Summary Only recently have the important biomarker capacities of microRNAs (miRNAs) in blood samples during disease been revealed. miRNAs are abundantly detected in circulation, and are less prone to degradation than longer RNA. Details regarding potential discriminatory miRNAs against numerous pathologic conditions are dispersed across articles, while existing resources that catalogue miRNA abundance in blood samples are not tailored to biomarker research. This study presents the meticulous manual curation of more than 200 articles that specifically interrogate the biomarker potential of miRNAs in whole blood, serum, or plasma. This annotation effort resulted in the creation of plasmiR, a database that systematically provides experimental evidence for the diagnostic and prognostic potential of circulating miRNAs against human diseases. plasmiR features 1021 entries, accompanied by rich study-specific meta-information, and an intuitive interface that enables the formation of complex queries and visualizations. Abstract Only recently, microRNAs (miRNAs) were found to exist in traceable and distinctive amounts in the human circulatory system, bringing forth the intriguing possibility of using them as minimally invasive biomarkers. miRNAs are short non-coding RNAs that act as potent post-transcriptional regulators of gene expression. Extensive studies in cancer and other disease landscapes investigate the protective/pathogenic functions of dysregulated miRNAs, as well as their biomarker potential. A specialized resource amassing experimentally verified, circulating miRNA biomarkers does not exist. We queried the existing literature to identify articles assessing diagnostic/prognostic roles of miRNAs in blood, serum, or plasma samples. Articles were scrutinized in order to exclude instances lacking sufficient experimental documentation or employing no biomarker assessment methods. We incorporated information from more than 200 biomedical articles, annotating crucial meta-information including cohort sizes, inclusion-exclusion criteria, disease/healthy confirmation methods and quantification details. miRNAs and diseases were systematically characterized using reference resources. Our circulating miRNA biomarker collection is provided as an online database, plasmiR. It consists of 1021 entries regarding 251 miRNAs and 112 diseases. More than half of plasmiR’s entries refer to cancerous and neoplastic conditions, 183 of them (32%) describing prognostic associations. plasmiR facilitates smart queries, emphasizing visualization and exploratory modes for all researchers.
Cancers arrow_drop_down CancersOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-6694/13/15/3680/pdfadd 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=10.3390/cancers13153680&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routesgold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Cancers arrow_drop_down CancersOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-6694/13/15/3680/pdfadd 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=10.3390/cancers13153680&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Netherlands EnglishPublisher:MDPI AG Maria Vasilarou; Nikolaos Alachiotis; Joanna Garefalaki; Apostolos Beloukas; Pavlos Pavlidis;Full-genome-sequence computational analyses of the SARS-coronavirus (CoV)-2 genomes allow us to understand the evolutionary events and adaptability mechanisms. We used population genetics analyses on human SARS-CoV-2 genomes available on 2 April 2020 to infer the mutation rate and plausible recombination events between the Betacoronavirus genomes in nonhuman hosts that may have contributed to the evolution of SARS-CoV-2. Furthermore, we localized the targets of recent and strong, positive selection during the first pandemic wave. The genomic regions that appear to be under positive selection are largely co-localized with regions in which recombination from nonhuman hosts took place. Our results suggest that the pangolin coronavirus genome may have contributed to the SARS-CoV-2 genome by recombination with the bat coronavirus genome. However, we find evidence for additional recombination events that involve coronavirus genomes from other hosts, i.e., hedgehogs and sparrows. We further infer that recombination may have recently occurred within human hosts. Finally, we estimate the parameters of a demographic scenario involving an exponential growth of the size of the SARS-CoV-2 populations that have infected European, Asian, and Northern American cohorts, and we demonstrate that a rapid exponential growth in population size from the first wave can support the observed polymorphism patterns in SARS-CoV-2 genomes.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC7914631Data sources: PubMed CentralLifeOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2075-1729/11/2/129/pdfadd 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=10.3390/life11020129&type=result"></script>'); --> </script>
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 . 2021Full-Text: http://europepmc.org/articles/PMC7914631Data sources: PubMed CentralLifeOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2075-1729/11/2/129/pdfadd 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=10.3390/life11020129&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 EnglishPublisher:MDPI AG Athanasios Alexiou; Dimitrios Zisis; Ioannis Kavakiotis; Marios Miliotis; Antonis Koussounadis; Dimitra Karagkouni; Artemis G. Hatzigeorgiou;microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7823405Data sources: PubMed CentralGenesOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4425/12/1/46/pdfadd 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=10.3390/genes12010046&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 9 citations 9 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/PMC7823405Data sources: PubMed CentralGenesOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4425/12/1/46/pdfadd 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=10.3390/genes12010046&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France, Italy, France, FrancePublisher:Rockefeller University Press Funded by:INCa, EC | INSPIREDINCa ,EC| INSPIREDAuthors: Sicari, Daria; Chatziioannou, Aristotelis; Koutsandreas, Theodoros; Sitia, Roberto; +1 AuthorsSicari, Daria; Chatziioannou, Aristotelis; Koutsandreas, Theodoros; Sitia, Roberto; Chevet, Eric;pmc: PMC7480093 , PMC7480111
handle: 20.500.11768/101728 , 20.500.11768/101727
Similar to other RNA viruses, SARS-CoV-2 must (1) enter a target/host cell, (2) reprogram it to ensure its replication, (3) exit the host cell, and (4) repeat this cycle for exponential growth. During the exit step, the virus hijacks the sophisticated machineries that host cells employ to correctly fold, assemble, and transport proteins along the exocytic pathway. Therefore, secretory pathway–mediated assemblage and excretion of infective particles represent appealing targets to reduce the efficacy of virus biogenesis, if not to block it completely. Here, we analyze and discuss the contribution of the molecular machines operating in the early secretory pathway in the biogenesis of SARS-CoV-2 and their relevance for potential antiviral targeting. The fact that these molecular machines are conserved throughout evolution, together with the redundancy and tissue specificity of their components, provides opportunities in the search for unique proteins essential for SARS-CoV-2 biology that could also be targeted with therapeutic objectives. Finally, we provide an overview of recent evidence implicating proteins of the early secretory pathway as potential antiviral targets with effective therapeutic applications. Sicari et al. discuss the early secretory pathway in the SARS-CoV-2 infection cycle and provide a perspective on potential therapeutic implications.
The Journal of Cell ... arrow_drop_down The Journal of Cell BiologyArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480093Data sources: PubMed CentralThe Journal of Cell Biology; Hal-DiderotArticle . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480111Data sources: PubMed CentralThe Journal of Cell BiologyOther literature type . Article . 2020 . Peer-reviewedLicense: CC BY NC SAArchivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele; The Journal of Cell BiologyArticle . 2020 . Peer-reviewedLicense: CC BYadd 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=10.1083/jcb.202006005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 63 citations 63 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert The Journal of Cell ... arrow_drop_down The Journal of Cell BiologyArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480093Data sources: PubMed CentralThe Journal of Cell Biology; Hal-DiderotArticle . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480111Data sources: PubMed CentralThe Journal of Cell BiologyOther literature type . Article . 2020 . Peer-reviewedLicense: CC BY NC SAArchivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele; The Journal of Cell BiologyArticle . 2020 . Peer-reviewedLicense: CC BYadd 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=10.1083/jcb.202006005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Other literature type , Presentation 2020Publisher:Research Square Platform LLC Authors: Nikolaos Pechlivanis; Maria Tsagiopoulou; Fotis Psomopoulos;Nikolaos Pechlivanis; Maria Tsagiopoulou; Fotis Psomopoulos;Abstract Background: The integration of multi-omics data can greatly facilitate the advancement of research in Life Sciences by providing new insights on how biological systems interact. However, there is currently no widespread procedure for a robust, efficient and meaningful multi-omics data integration; the approach presented here is a first attempt towards increasing the reliability of data discovery power compared to the processing of individual biodata sets. Results: Here, we proposed a high-speed framework, called InterTADs, for integrating multi-omics data from the same physical source (e.g. patient) taking into account the chromatin configuration of the genome, i.e. the topologically associating domains (TADs). The main concept of the proposed methodology is to create a single matrix with all different events (e.g. DNA methylation, expression, mutation) combined with their genome coordinates and the respective quantitative metrics after application of the appropriate scaling. The events are divided into their related TADs according to the chromosomal location and each TAD is evaluated for statistically significant differences between the groups of interest (e.g. normal cells vs cancer cells). Finally, several visualization approaches are available, including the mapping of the events on the chromosomal location of the TAD as well as the distribution of the counts within a given TAD across the different study groups.Conclusions: InterTADs provides a general framework for integrating multi omics data and relating them with the TADs. This could lead to the extraction of new biological insight of the examined case study. InterTADs is an open-source tool implemented in R and licensed under the MIT License. The source code is freely available from https://github.com/nikopech/InterTADs.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 35visibility views 35 download downloads 23 Powered bymore_vert add 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.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type 2020Publisher:ACM Authors: Konstantinos Zagganas; Thanasis Vergoulis; Spiros Skiadopoulos; Theodore Dalamagas;Konstantinos Zagganas; Thanasis Vergoulis; Spiros Skiadopoulos; Theodore Dalamagas;Investigating whether two different classifications of a population are associated, is an interesting problem in many scientific fields. For this reason, various statistical tests to reveal this type of associations have been developed, with the most popular of them being Fisher's exact test. However it has lately been shown that in some cases this test fails to produce accurate results. An alternative approach, known as randomization tests, was introduced to alleviate this issue, however, such tests are computationally intensive. In this paper, we introduce two novel indexing approaches that exploit frequently occurring patterns in classifications to avoid performing redundant computations during the analysis. We conduct a comprehensive set of experiments using real datasets and application scenarios to show that our approaches always outperform the state-of-the-art, with one approach being faster by an order of magnitude. Funding: This work was partially funded by project “ELIXIR-GR”. The “ELIXIR-GR: Managing and Analysing Life Sciences Data (MIS:5002780)”Project is co-financed by Greece and the European Union - Euro-pean Regional Development Fund.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 19visibility views 19 download downloads 74 Powered bymore_vert add 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.eudescription 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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description Publicationkeyboard_double_arrow_right Article 2023 SwitzerlandPublisher:MDPI AG Funded by:EC | CY-BIOBANKEC| CY-BIOBANKAuthors: Vasileios L. Zogopoulos; Apostolos Malatras; Konstantinos Kyriakidis; Chrysanthi Charalampous; +10 AuthorsVasileios L. Zogopoulos; Apostolos Malatras; Konstantinos Kyriakidis; Chrysanthi Charalampous; Evanthia A. Makrygianni; Stéphanie Duguez; Marianna A. Koutsi; Marialena Pouliou; Christos Vasileiou; William J. Duddy; Marios Agelopoulos; George P. Chrousos; Vassiliki A. Iconomidou; Ioannis Michalopoulos;handle: 20.500.11850/599339
Genes with similar expression patterns in a set of diverse samples may be considered coexpressed. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. It offers a simple and intuitive website design and user interface, as well as an API endpoint. ISSN:2073-4409 Cells, 12 (3)
Cells arrow_drop_down CellsOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-4409/12/3/388/pdfadd 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 1 citations 1 popularity Average influence Average impulse Average Powered by BIP!more_vert Cells arrow_drop_down CellsOther literature type . Article . 2023 . Peer-reviewedLicense: CC BYFull-Text: https://www.mdpi.com/2073-4409/12/3/388/pdfadd 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 2021 Serbia, Belgium, France, France, Italy, Denmark, Italy, FrancePublisher:Oxford University Press (OUP) Funded by:MESTD | Ministry of Education, Sc..., EC | SMILE, NIH | Gene Ontology Consortium +3 projectsMESTD| Ministry of Education, Science and Technological Development, Republic of Serbia, Grant no. 451-03-68/2020-14/200017 (University of Belgrade, Institute of Nuclear Sciences 'Vinca', Belgrade-Vinca) ,EC| SMILE ,NIH| Gene Ontology Consortium ,EC| IDPfun ,EC| MIMIC ,EC| PhasAGEFederica Quaglia; Bálint Mészáros; Edoardo Salladini; András Hatos; Rita Pancsa; Lucía B. Chemes; Mátyás Pajkos; Tamas Lazar; Samuel Peña-Díaz; Jaime Santos; Veronika Ács; Nazanin Farahi; Erzsébet Fichó; Maria Cristina Aspromonte; Claudio Bassot; Anastasia Chasapi; Norman E. Davey; Radoslav Davidovic; László Dobson; Arne Elofsson; Gábor Erdős; Pascale Gaudet; Michelle G. Giglio; Juliana Glavina; Javier Iserte; Valentin Iglesias; Zsofia E. Kalman; Matteo Lambrughi; Emanuela Leonardi; Sonia Longhi; Sandra Macedo-Ribeiro; Emiliano Maiani; Julia Marchetti; Cristina Marino-Buslje; Attila Mészáros; Alexander Miguel Monzon; Giovanni Minervini; Suvarna Nadendla; Juliet F Nilsson; Marian Novotný; Christos A. Ouzounis; Nicolas Palopoli; Elena Papaleo; Pedro Pereira; Gabriele Pozzati; Vasilis J. Promponas; Jordi Pujols; Alma Carolina Sanchez Rocha; Martín N. Salas; Luciana Rodriguez Sawicki; Eva Schad; Aditi Shenoy; Tamás Szaniszló; Konstantinos D. Tsirigos; Nevena Veljkovic; Gustavo Parisi; Salvador Ventura; Zsuzsanna Dosztányi; Peter Tompa; Silvio C. E. Tosatto; Damiano Piovesan;The Database of Intrinsically Disordered Proteins (DisProt, URL: https://disprot.org) is the major repository of manually curated annotations of intrinsically disordered proteins and regions from the literature. We report here recent updates of DisProt version 9, including a restyled web interface, refactored Intrinsically Disordered Proteins Ontology (IDPO), improvements in the curation process and significant content growth of around 30%. Higher quality and consistency of annotations is provided by a newly implemented reviewing process and training of curators. The increased curation capacity is fostered by the integration of DisProt with APICURON, a dedicated resource for the proper attribution and recognition of biocuration efforts. Better interoperability is provided through the adoption of the Minimum Information About Disorder (MIADE) standard, an active collaboration with the Gene Ontology (GO) and Evidence and Conclusion Ontology (ECO) consortia and the support of the ELIXIR infrastructure. © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.
Archivio Istituziona... arrow_drop_down Archivio Istituzionale (AperTO); Nucleic Acids Research; Archivio istituzionale della ricerca - Università di Padova; Vrije Universiteit Brussel Research PortalOther literature type . Article . 2022 . 2021 . Peer-reviewedLicense: CC BYEurope PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8728214Data sources: PubMed CentralOnline Research Database In TechnologyArticle . 2022Data sources: Online Research Database In TechnologyHAL Descartes; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2022License: CC BY NCFull-Text: https://hal.science/hal-03463975/documentadd 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/nar/gkab1082&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 100 citations 100 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!visibility 71visibility views 71 download downloads 76 Powered bymore_vert Archivio Istituziona... arrow_drop_down Archivio Istituzionale (AperTO); Nucleic Acids Research; Archivio istituzionale della ricerca - Università di Padova; Vrije Universiteit Brussel Research PortalOther literature type . Article . 2022 . 2021 . Peer-reviewedLicense: CC BYEurope PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8728214Data sources: PubMed CentralOnline Research Database In TechnologyArticle . 2022Data sources: Online Research Database In TechnologyHAL Descartes; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2022License: CC BY NCFull-Text: https://hal.science/hal-03463975/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=10.1093/nar/gkab1082&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021 Czech RepublicPublisher:Oxford University Press (OUP) Funded by:EC | OBERON, EC | HBM4EUEC| OBERON ,EC| HBM4EUFlorence Jornod; Thomas Jaylet; Ludek Blaha; Denis Sarigiannis; Luc Tamisier; Karine Audouze;Abstract Motivation Adverse outcome pathways (AOPs) are a conceptual framework developed to support the use of alternative toxicology approaches in the risk assessment. AOPs are structured linear organizations of existing knowledge illustrating causal pathways from the initial molecular perturbation triggered by various stressors, through key events (KEs) at different levels of biology, to the ultimate health or ecotoxicological adverse outcome. Results Artificial intelligence can be used to systematically explore available toxicological data that can be parsed in the scientific literature. Recently, a tool called AOP-helpFinder was developed to identify associations between stressors and KEs supporting thus documentation of AOPs. To facilitate the utilization of this advanced bioinformatics tool by the scientific and the regulatory community, a webserver was created. The proposed AOP-helpFinder webserver uses better performing version of the tool which reduces the need for manual curation of the obtained results. As an example, the server was successfully applied to explore relationships of a set of endocrine disruptors with metabolic-related events. The AOP-helpFinder webserver assists in a rapid evaluation of existing knowledge stored in the PubMed database, a global resource of scientific information, to build AOPs and Adverse Outcome Networks supporting the chemical risk assessment. Availability and implementation AOP-helpFinder is available at http://aop-helpfinder.u-paris-sciences.fr/index.php Supplementary information Supplementary data are available at Bioinformatics online.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8796376Data sources: PubMed CentralUniverzitní repozitář Masarykovy univerzityArticle . 2022Data sources: Univerzitní repozitář Masarykovy univerzityadd 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 25 citations 25 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC8796376Data sources: PubMed CentralUniverzitní repozitář Masarykovy univerzityArticle . 2022Data sources: Univerzitní repozitář Masarykovy univerzityadd 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/bioinformatics/btab750&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2021Publisher:MDPI AG Spyros Tastsoglou; Marios Miliotis; Ioannis Kavakiotis; Athanasios Alexiou; Eleni C. Gkotsi; Anastasia Lambropoulou; Vasileios Lygnos; Vasiliki Kotsira; Vasileios Maroulis; Dimitrios Zisis; Giorgos Skoufos; Artemis G. Hatzigeorgiou;Simple Summary Only recently have the important biomarker capacities of microRNAs (miRNAs) in blood samples during disease been revealed. miRNAs are abundantly detected in circulation, and are less prone to degradation than longer RNA. Details regarding potential discriminatory miRNAs against numerous pathologic conditions are dispersed across articles, while existing resources that catalogue miRNA abundance in blood samples are not tailored to biomarker research. This study presents the meticulous manual curation of more than 200 articles that specifically interrogate the biomarker potential of miRNAs in whole blood, serum, or plasma. This annotation effort resulted in the creation of plasmiR, a database that systematically provides experimental evidence for the diagnostic and prognostic potential of circulating miRNAs against human diseases. plasmiR features 1021 entries, accompanied by rich study-specific meta-information, and an intuitive interface that enables the formation of complex queries and visualizations. Abstract Only recently, microRNAs (miRNAs) were found to exist in traceable and distinctive amounts in the human circulatory system, bringing forth the intriguing possibility of using them as minimally invasive biomarkers. miRNAs are short non-coding RNAs that act as potent post-transcriptional regulators of gene expression. Extensive studies in cancer and other disease landscapes investigate the protective/pathogenic functions of dysregulated miRNAs, as well as their biomarker potential. A specialized resource amassing experimentally verified, circulating miRNA biomarkers does not exist. We queried the existing literature to identify articles assessing diagnostic/prognostic roles of miRNAs in blood, serum, or plasma samples. Articles were scrutinized in order to exclude instances lacking sufficient experimental documentation or employing no biomarker assessment methods. We incorporated information from more than 200 biomedical articles, annotating crucial meta-information including cohort sizes, inclusion-exclusion criteria, disease/healthy confirmation methods and quantification details. miRNAs and diseases were systematically characterized using reference resources. Our circulating miRNA biomarker collection is provided as an online database, plasmiR. It consists of 1021 entries regarding 251 miRNAs and 112 diseases. More than half of plasmiR’s entries refer to cancerous and neoplastic conditions, 183 of them (32%) describing prognostic associations. plasmiR facilitates smart queries, emphasizing visualization and exploratory modes for all researchers.
Cancers arrow_drop_down CancersOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-6694/13/15/3680/pdfadd 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 Routesgold 8 citations 8 popularity Top 10% influence Average impulse Top 10% Powered by BIP!more_vert Cancers arrow_drop_down CancersOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2072-6694/13/15/3680/pdfadd 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 2021 Netherlands EnglishPublisher:MDPI AG Maria Vasilarou; Nikolaos Alachiotis; Joanna Garefalaki; Apostolos Beloukas; Pavlos Pavlidis;Full-genome-sequence computational analyses of the SARS-coronavirus (CoV)-2 genomes allow us to understand the evolutionary events and adaptability mechanisms. We used population genetics analyses on human SARS-CoV-2 genomes available on 2 April 2020 to infer the mutation rate and plausible recombination events between the Betacoronavirus genomes in nonhuman hosts that may have contributed to the evolution of SARS-CoV-2. Furthermore, we localized the targets of recent and strong, positive selection during the first pandemic wave. The genomic regions that appear to be under positive selection are largely co-localized with regions in which recombination from nonhuman hosts took place. Our results suggest that the pangolin coronavirus genome may have contributed to the SARS-CoV-2 genome by recombination with the bat coronavirus genome. However, we find evidence for additional recombination events that involve coronavirus genomes from other hosts, i.e., hedgehogs and sparrows. We further infer that recombination may have recently occurred within human hosts. Finally, we estimate the parameters of a demographic scenario involving an exponential growth of the size of the SARS-CoV-2 populations that have infected European, Asian, and Northern American cohorts, and we demonstrate that a rapid exponential growth in population size from the first wave can support the observed polymorphism patterns in SARS-CoV-2 genomes.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2021Full-Text: http://europepmc.org/articles/PMC7914631Data sources: PubMed CentralLifeOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2075-1729/11/2/129/pdfadd 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=10.3390/life11020129&type=result"></script>'); --> </script>
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 . 2021Full-Text: http://europepmc.org/articles/PMC7914631Data sources: PubMed CentralLifeOther literature type . Article . 2021 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2075-1729/11/2/129/pdfadd 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=10.3390/life11020129&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 EnglishPublisher:MDPI AG Athanasios Alexiou; Dimitrios Zisis; Ioannis Kavakiotis; Marios Miliotis; Antonis Koussounadis; Dimitra Karagkouni; Artemis G. Hatzigeorgiou;microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7823405Data sources: PubMed CentralGenesOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4425/12/1/46/pdfadd 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=10.3390/genes12010046&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 9 citations 9 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/PMC7823405Data sources: PubMed CentralGenesOther literature type . Article . 2020 . Peer-reviewedLicense: CC BYFull-Text: http://www.mdpi.com/2073-4425/12/1/46/pdfadd 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=10.3390/genes12010046&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2020 France, Italy, France, FrancePublisher:Rockefeller University Press Funded by:INCa, EC | INSPIREDINCa ,EC| INSPIREDAuthors: Sicari, Daria; Chatziioannou, Aristotelis; Koutsandreas, Theodoros; Sitia, Roberto; +1 AuthorsSicari, Daria; Chatziioannou, Aristotelis; Koutsandreas, Theodoros; Sitia, Roberto; Chevet, Eric;pmc: PMC7480093 , PMC7480111
handle: 20.500.11768/101728 , 20.500.11768/101727
Similar to other RNA viruses, SARS-CoV-2 must (1) enter a target/host cell, (2) reprogram it to ensure its replication, (3) exit the host cell, and (4) repeat this cycle for exponential growth. During the exit step, the virus hijacks the sophisticated machineries that host cells employ to correctly fold, assemble, and transport proteins along the exocytic pathway. Therefore, secretory pathway–mediated assemblage and excretion of infective particles represent appealing targets to reduce the efficacy of virus biogenesis, if not to block it completely. Here, we analyze and discuss the contribution of the molecular machines operating in the early secretory pathway in the biogenesis of SARS-CoV-2 and their relevance for potential antiviral targeting. The fact that these molecular machines are conserved throughout evolution, together with the redundancy and tissue specificity of their components, provides opportunities in the search for unique proteins essential for SARS-CoV-2 biology that could also be targeted with therapeutic objectives. Finally, we provide an overview of recent evidence implicating proteins of the early secretory pathway as potential antiviral targets with effective therapeutic applications. Sicari et al. discuss the early secretory pathway in the SARS-CoV-2 infection cycle and provide a perspective on potential therapeutic implications.
The Journal of Cell ... arrow_drop_down The Journal of Cell BiologyArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480093Data sources: PubMed CentralThe Journal of Cell Biology; Hal-DiderotArticle . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480111Data sources: PubMed CentralThe Journal of Cell BiologyOther literature type . Article . 2020 . Peer-reviewedLicense: CC BY NC SAArchivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele; The Journal of Cell BiologyArticle . 2020 . Peer-reviewedLicense: CC BYadd 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=10.1083/jcb.202006005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 63 citations 63 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert The Journal of Cell ... arrow_drop_down The Journal of Cell BiologyArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480093Data sources: PubMed CentralThe Journal of Cell Biology; Hal-DiderotArticle . 2020Europe PubMed CentralArticle . 2020Full-Text: http://europepmc.org/articles/PMC7480111Data sources: PubMed CentralThe Journal of Cell BiologyOther literature type . Article . 2020 . Peer-reviewedLicense: CC BY NC SAArchivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele; The Journal of Cell BiologyArticle . 2020 . Peer-reviewedLicense: CC BYadd 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=10.1083/jcb.202006005&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Other literature type , Presentation 2020Publisher:Research Square Platform LLC Authors: Nikolaos Pechlivanis; Maria Tsagiopoulou; Fotis Psomopoulos;Nikolaos Pechlivanis; Maria Tsagiopoulou; Fotis Psomopoulos;Abstract Background: The integration of multi-omics data can greatly facilitate the advancement of research in Life Sciences by providing new insights on how biological systems interact. However, there is currently no widespread procedure for a robust, efficient and meaningful multi-omics data integration; the approach presented here is a first attempt towards increasing the reliability of data discovery power compared to the processing of individual biodata sets. Results: Here, we proposed a high-speed framework, called InterTADs, for integrating multi-omics data from the same physical source (e.g. patient) taking into account the chromatin configuration of the genome, i.e. the topologically associating domains (TADs). The main concept of the proposed methodology is to create a single matrix with all different events (e.g. DNA methylation, expression, mutation) combined with their genome coordinates and the respective quantitative metrics after application of the appropriate scaling. The events are divided into their related TADs according to the chromosomal location and each TAD is evaluated for statistically significant differences between the groups of interest (e.g. normal cells vs cancer cells). Finally, several visualization approaches are available, including the mapping of the events on the chromosomal location of the TAD as well as the distribution of the counts within a given TAD across the different study groups.Conclusions: InterTADs provides a general framework for integrating multi omics data and relating them with the TADs. This could lead to the extraction of new biological insight of the examined case study. InterTADs is an open-source tool implemented in R and licensed under the MIT License. The source code is freely available from https://github.com/nikopech/InterTADs.
add 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=10.21203/rs.3.rs-54194/v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 35visibility views 35 download downloads 23 Powered bymore_vert add 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=10.21203/rs.3.rs-54194/v1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type 2020Publisher:ACM Authors: Konstantinos Zagganas; Thanasis Vergoulis; Spiros Skiadopoulos; Theodore Dalamagas;Konstantinos Zagganas; Thanasis Vergoulis; Spiros Skiadopoulos; Theodore Dalamagas;Investigating whether two different classifications of a population are associated, is an interesting problem in many scientific fields. For this reason, various statistical tests to reveal this type of associations have been developed, with the most popular of them being Fisher's exact test. However it has lately been shown that in some cases this test fails to produce accurate results. An alternative approach, known as randomization tests, was introduced to alleviate this issue, however, such tests are computationally intensive. In this paper, we introduce two novel indexing approaches that exploit frequently occurring patterns in classifications to avoid performing redundant computations during the analysis. We conduct a comprehensive set of experiments using real datasets and application scenarios to show that our approaches always outperform the state-of-the-art, with one approach being faster by an order of magnitude. Funding: This work was partially funded by project “ELIXIR-GR”. The “ELIXIR-GR: Managing and Analysing Life Sciences Data (MIS:5002780)”Project is co-financed by Greece and the European Union - Euro-pean Regional Development Fund.
add 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=10.1145/3400903.3400923&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!visibility 19visibility views 19 download downloads 74 Powered bymore_vert add 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=10.1145/3400903.3400923&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription 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.
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.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.eu