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300 results on '"Gaudet, Pascale"'

1. Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

Author

Toro, Sabrina, Anagnostopoulos, Anna V, Bello, Sue, Blumberg, Kai, Cameron, Rhiannon, Carmody, Leigh, Diehl, Alexander D, Dooley, Damion, Duncan, William, Fey, Petra, Gaudet, Pascale, Harris, Nomi L, Joachimiak, Marcin, Kiani, Leila, Lubiana, Tiago, Munoz-Torres, Monica C, O'Neil, Shawn, Osumi-Sutherland, David, Puig, Aleix, Reese, Justin P, Reiser, Leonore, Robb, Sofia, Ruemping, Troy, Seager, James, Sid, Eric, Stefancsik, Ray, Weber, Magalie, Wood, Valerie, Haendel, Melissa A, and Mungall, Christopher J

Subjects
Computer Science - Artificial Intelligence
Abstract

Background: Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources. Results: We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues. Conclusions: These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Published
2023

2. The Gene Ontology knowledgebase in 2023

Author

Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D’Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, and Berardini, Tanya Z

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, 1.1 Normal biological development and functioning, Underpinning research, Gene Ontology, Proteins, Molecular Sequence Annotation, Databases, Genetic, Computational Biology, gene annotation, gene function, knowledgebase, knowledge graphs, Gene Ontology Consortium, Developmental Biology, Biochemistry and cell biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

4. Perinatal morbidity among women with a previous caesarean delivery (PRISMA trial): a cluster-randomised trial

Author

Chaillet, Nils, Mâsse, Benoît, Grobman, William A, Shorten, Allison, Gauthier, Robert, Rozenberg, Patrick, Dugas, Marylène, Pasquier, Jean-Charles, Audibert, François, Abenhaim, Haim A, Demers, Suzanne, Piedboeuf, Bruno, Fraser, William D, Gagnon, Robert, Gagné, Guy-Paul, Francoeur, Diane, Girard, Isabelle, Duperron, Louise, Bédard, Marie-Josée, Johri, Mira, Dubé, Eric, Blouin, Simon, Ducruet, Thierry, Girard, Mario, Bujold, Emmanuel, Roy, Chantal, Mailhot, Josée, Samson, Anne, Bordeleau, Cathie, Aboulfadl, Siham, Nadeau, Gabrielle, Arpin, Catherine, Trudeau, Angèle, Champagne, Eugénie, Cassivi, Margaux, Rajaobelison, Gentiane, Marsan, Francine, Brière, Cristelle, Gimeno, Ana Gil, Platt, Robert, Liu, Shiliang, Althabe, Fernando, Champagne, François, Blake, Jennifer, Gagnon, Andrée, Dart, Kim, Ciofani, Luisa, Laurent, Marie-Eve St, Riverin, Daniel, Joshi, Arvind K, Lévesque, Isabelle, Mailloux, Jacques, Beaudoin, François, Monnier, Patricia, Tordjman, Laurent, Bédard, Natacha, Dorval, Gaston, Carpentier, Caroline, Lemieux, Réjean, Roberge, Suzanne, Simard, Martine, Bedrossain, Roupen, Landry, Gérard, Perreault, Gilles, Aubé, Marie-Hélène, Bibeau, Jean-Guy, Desautels, Pascale, Paradis, Eric, Hébert, Josée, Beaumont, Marie-Claude, Gaudet, Pascale, Turbide, Manon, Hétu, Valérie, Major, Brigitte, Carette, Marie-Eve, Dupont-Chalaoui, Katrie, Blais, Francine, Garcia, Dario, Gervaise, Amélie, Poungui, Lionel, Boily, Nathalie, Dubois, Emmanuelle, Hamel, Annick, Isoard, Lionel-André, Leduc-Arbour, Nathaël, Montini, Alexandre, Bossé, Stéphanie, Faucher, Elise, Gravel, Serge, Poirier, Isabelle, Hemmings, Robert, Saxon, Daniel, Engel, Francis, Goyet, Martine, Cantin, Jérôme, Charest, Nicole, Gervais, Carolyne, Malenfant, Sylvain, Raymond, Chantal, St-Pierre, Luc, Lemieux, Marie-Claude, Torjman, Laurent, Labelle, Geneviève, Waddell, Guy, Miner, Louise, Tulandi, Togas, Gagnon, Sonia, Fisch, Patricia, Gagné, Suzanne, Gagné, Alexandra, Guérin, Pascale, and Laforge, Marlène

Published
2024
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5. The Minimum Information about a Molecular Interaction Causal Statement (MI2CAST)

Author

Touré, Vasundra, Vercruysse, Steven, Acencio, Marcio Luis, Lovering, Ruth C, Orchard, Sandra, Bradley, Glyn, Casals-Casas, Cristina, Chaouiya, Claudine, del-Toro, Noemi, Flobak, Åsmund, Gaudet, Pascale, Hermjakob, Henning, Hoyt, Charles Tapley, Licata, Luana, Lægreid, Astrid, Mungall, Christopher J, Niknejad, Anne, Panni, Simona, Perfetto, Livia, Porras, Pablo, Pratt, Dexter, Saez-Rodriguez, Julio, Thieffry, Denis, Thomas, Paul D, Türei, Dénes, and Kuiper, Martin

Subjects
Generic health relevance, Causality, Humans, Software, Mathematical Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

MotivationA large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources.ResultsHere, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources.Availability and implementationThe checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST.Supplementary informationSupplementary data are available at Bioinformatics online.

Published
2021

6. Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns.

Author

Wood, Valerie, Carbon, Seth, Harris, Midori A, Lock, Antonia, Engel, Stacia R, Hill, David P, Van Auken, Kimberly, Attrill, Helen, Feuermann, Marc, Gaudet, Pascale, Lovering, Ruth C, Poux, Sylvain, Rutherford, Kim M, and Mungall, Christopher J

Subjects
annotation, biocuration, gene ontology, quality control, Biochemistry and Cell Biology, Microbiology, Immunology
Abstract

Biological processes are accomplished by the coordinated action of gene products. Gene products often participate in multiple processes, and can therefore be annotated to multiple Gene Ontology (GO) terms. Nevertheless, processes that are functionally, temporally and/or spatially distant may have few gene products in common, and co-annotation to unrelated processes probably reflects errors in literature curation, ontology structure or automated annotation pipelines. We have developed an annotation quality control workflow that uses rules based on mutually exclusive processes to detect annotation errors, based on and validated by case studies including the three we present here: fission yeast protein-coding gene annotations over time; annotations for cohesin complex subunits in human and model species; and annotations using a selected set of GO biological process terms in human and five model species. For each case study, we reviewed available GO annotations, identified pairs of biological processes which are unlikely to be correctly co-annotated to the same gene products (e.g. amino acid metabolism and cytokinesis), and traced erroneous annotations to their sources. To date we have generated 107 quality control rules, and corrected 289 manual annotations in eukaryotes and over 52 700 automatically propagated annotations across all taxa.

Published
2020

7. Gene Ontology Causal Activity Modeling (GO-CAM) moves beyond GO annotations to structured descriptions of biological functions and systems

Author

Thomas, Paul D, Hill, David P, Mi, Huaiyu, Osumi-Sutherland, David, Van Auken, Kimberly, Carbon, Seth, Balhoff, James P, Albou, Laurent-Philippe, Good, Benjamin, Gaudet, Pascale, Lewis, Suzanna E, and Mungall, Christopher J

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Networking and Information Technology R&D (NITRD), Computational Biology, Databases, Genetic, Gene Ontology, Humans, Models, Biological, Molecular Sequence Annotation, Phenotype, Signal Transduction, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To increase the utility of Gene Ontology annotations for interpretation of genome-wide experimental data, we have developed GO-CAM, a structured framework for linking multiple GO annotations into an integrated model of a biological system. We expect that GO-CAM will enable new applications in pathway and network analysis as well as improving standard GO annotations for traditional GO-based applications.

Published
2019

8. ECO, the Evidence & Conclusion Ontology: community standard for evidence information

Author

Giglio, Michelle, Tauber, Rebecca, Nadendla, Suvarna, Munro, James, Olley, Dustin, Ball, Shoshannah, Mitraka, Elvira, Schriml, Lynn M, Gaudet, Pascale, Hobbs, Elizabeth T, Erill, Ivan, Siegele, Deborah A, Hu, James C, Mungall, Chris, and Chibucos, Marcus C

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Animals, Computational Biology, Databases, Genetic, Gene Ontology, Humans, Information Storage and Retrieval, Internet, Proteins, Sequence Analysis, Protein, User-Computer Interface, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences
Abstract

The Evidence and Conclusion Ontology (ECO) contains terms (classes) that describe types of evidence and assertion methods. ECO terms are used in the process of biocuration to capture the evidence that supports biological assertions (e.g. gene product X has function Y as supported by evidence Z). Capture of this information allows tracking of annotation provenance, establishment of quality control measures and query of evidence. ECO contains over 1500 terms and is in use by many leading biological resources including the Gene Ontology, UniProt and several model organism databases. ECO is continually being expanded and revised based on the needs of the biocuration community. The ontology is freely available for download from GitHub (https://github.com/evidenceontology/) or the project's website (http://evidenceontology.org/). Users can request new terms or changes to existing terms through the project's GitHub site. ECO is released into the public domain under CC0 1.0 Universal.

Published
2019

9. Gene Ontology: Pitfalls, Biases, Remedies

Author

Gaudet, Pascale and Dessimoz, Christophe

Subjects
Quantitative Biology - Genomics
Abstract

The Gene Ontology (GO) is a formidable resource but there are several considerations about it that are essential to understand the data and interpret it correctly. The GO is sufficiently simple that it can be used without deep understanding of its structure or how it is developed, which is both a strength and a weakness. In this chapter, we discuss some common misinterpretations of the ontology and the annotations. A better understanding of the pitfalls and the biases in the GO should help users make the most of this very rich resource. We also review some of the misconceptions and misleading assumptions commonly made about GO, including the effect of data incompleteness, the importance of annotation qualifiers, and the transitivity or lack thereof associated with different ontology relations. We also discuss several biases that can confound aggregate analyses such as gene enrichment analyses. For each of these pitfalls and biases, we suggest remedies and best practices., Comment: to appear in forthcoming book "The Gene Ontology Handbook" (Springer Humana)

Published
2016
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10. Primer on the Gene Ontology

Author

Gaudet, Pascale, Škunca, Nives, Hu, James C., and Dessimoz, Christophe

Subjects
Quantitative Biology - Genomics
Abstract

The Gene Ontology (GO) project is the largest resource for cataloguing gene function. The combination of solid conceptual underpinnings and a practical set of features have made the GO a widely adopted resource in the research community and an essential resource for data analysis. In this chapter, we provide a concise primer for all users of the GO. We briefly introduce the structure of the ontology and explain how to interpret annotations associated with the GO., Comment: to appear in forthcoming book "The Gene Ontology Handbook" (Springer Humana)

Published
2016
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11. The health care and life sciences community profile for dataset descriptions

Author

Dumontier, Michel, Gray, Alasdair JG, Marshall, M Scott, Alexiev, Vladimir, Ansell, Peter, Bader, Gary, Baran, Joachim, Bolleman, Jerven T, Callahan, Alison, Cruz-Toledo, José, Gaudet, Pascale, Gombocz, Erich A, Gonzalez-Beltran, Alejandra N, Groth, Paul, Haendel, Melissa, Ito, Maori, Jupp, Simon, Juty, Nick, Katayama, Toshiaki, Kobayashi, Norio, Krishnaswami, Kalpana, Laibe, Camille, Le Novère, Nicolas, Lin, Simon, Malone, James, Miller, Michael, Mungall, Christopher J, Rietveld, Laurens, Wimalaratne, Sarala M, and Yamaguchi, Atsuko

Subjects
Data Management and Data Science, Information and Computing Sciences, Biological Sciences, Bioinformatics and Computational Biology, Generic health relevance, Data profiling, Dataset descriptions, FAIR data, Metadata, Provenance, Medical and Health Sciences
Abstract

Access to consistent, high-quality metadata is critical to finding, understanding, and reusing scientific data. However, while there are many relevant vocabularies for the annotation of a dataset, none sufficiently captures all the necessary metadata. This prevents uniform indexing and querying of dataset repositories. Towards providing a practical guide for producing a high quality description of biomedical datasets, the W3C Semantic Web for Health Care and the Life Sciences Interest Group (HCLSIG) identified Resource Description Framework (RDF) vocabularies that could be used to specify common metadata elements and their value sets. The resulting guideline covers elements of description, identification, attribution, versioning, provenance, and content summarization. This guideline reuses existing vocabularies, and is intended to meet key functional requirements including indexing, discovery, exchange, query, and retrieval of datasets, thereby enabling the publication of FAIR data. The resulting metadata profile is generic and could be used by other domains with an interest in providing machine readable descriptions of versioned datasets.

Published
2016

12. Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

Author

Feuermann, Marc, Gaudet, Pascale, Mi, Huaiyu, Lewis, Suzanna E, and Thomas, Paul D

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Animals, Apoptosis, Autophagy, Evolution, Molecular, Gene Ontology, Humans, Models, Genetic, Molecular Sequence Annotation, Phylogeny, Software, Data Format, Library and Information Studies, Bioinformatics and computational biology, Data management and data science
Abstract

We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This 'GO Phylogenetic Annotation' approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo.

Published
2016

13. Perinatal morbidity among women with a previous caesarean delivery (PRISMA trial): a cluster-randomised trial

Author

Chaillet, Nils, primary, Mâsse, Benoît, additional, Grobman, William A, additional, Shorten, Allison, additional, Gauthier, Robert, additional, Rozenberg, Patrick, additional, Dugas, Marylène, additional, Pasquier, Jean-Charles, additional, Audibert, François, additional, Abenhaim, Haim A, additional, Demers, Suzanne, additional, Piedboeuf, Bruno, additional, Fraser, William D, additional, Gagnon, Robert, additional, Gagné, Guy-Paul, additional, Francoeur, Diane, additional, Girard, Isabelle, additional, Duperron, Louise, additional, Bédard, Marie-Josée, additional, Johri, Mira, additional, Dubé, Eric, additional, Blouin, Simon, additional, Ducruet, Thierry, additional, Girard, Mario, additional, Bujold, Emmanuel, additional, Chaillet, Nils, additional, Roy, Chantal, additional, Mailhot, Josée, additional, Samson, Anne, additional, Bordeleau, Cathie, additional, Aboulfadl, Siham, additional, Nadeau, Gabrielle, additional, Arpin, Catherine, additional, Trudeau, Angèle, additional, Champagne, Eugénie, additional, Cassivi, Margaux, additional, Rajaobelison, Gentiane, additional, Marsan, Francine, additional, Brière, Cristelle, additional, Gimeno, Ana Gil, additional, Platt, Robert, additional, Liu, Shiliang, additional, Althabe, Fernando, additional, Champagne, François, additional, Blake, Jennifer, additional, Gagnon, Andrée, additional, Dart, Kim, additional, Ciofani, Luisa, additional, Laurent, Marie-Eve St, additional, Riverin, Daniel, additional, Joshi, Arvind K, additional, Lévesque, Isabelle, additional, Mailloux, Jacques, additional, Beaudoin, François, additional, Monnier, Patricia, additional, Tordjman, Laurent, additional, Bédard, Natacha, additional, Dorval, Gaston, additional, Carpentier, Caroline, additional, Lemieux, Réjean, additional, Roberge, Suzanne, additional, Simard, Martine, additional, Bedrossain, Roupen, additional, Landry, Gérard, additional, Perreault, Gilles, additional, Aubé, Marie-Hélène, additional, Bibeau, Jean-Guy, additional, Desautels, Pascale, additional, Paradis, Eric, additional, Hébert, Josée, additional, Beaumont, Marie-Claude, additional, Gaudet, Pascale, additional, Turbide, Manon, additional, Hétu, Valérie, additional, Major, Brigitte, additional, Carette, Marie-Eve, additional, Dupont-Chalaoui, Katrie, additional, Blais, Francine, additional, Garcia, Dario, additional, Gervaise, Amélie, additional, Poungui, Lionel, additional, Boily, Nathalie, additional, Dubois, Emmanuelle, additional, Hamel, Annick, additional, Isoard, Lionel-André, additional, Leduc-Arbour, Nathaël, additional, Montini, Alexandre, additional, Bossé, Stéphanie, additional, Faucher, Elise, additional, Gravel, Serge, additional, Poirier, Isabelle, additional, Hemmings, Robert, additional, Saxon, Daniel, additional, Engel, Francis, additional, Goyet, Martine, additional, Cantin, Jérôme, additional, Charest, Nicole, additional, Gervais, Carolyne, additional, Malenfant, Sylvain, additional, Raymond, Chantal, additional, St-Pierre, Luc, additional, Lemieux, Marie-Claude, additional, Torjman, Laurent, additional, Labelle, Geneviève, additional, Waddell, Guy, additional, Miner, Louise, additional, Tulandi, Togas, additional, Gagnon, Sonia, additional, Fisch, Patricia, additional, Gagné, Suzanne, additional, Gagné, Alexandra, additional, Guérin, Pascale, additional, and Laforge, Marlène, additional

Published
2023
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15. The Gene Ontology knowledgebase in 2023

Author

Gene Ontology Consortium, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Luna Buitrago, Diana, Erdol, Meltem N, Gage, Matthew C, Ali Kadhum, Mohamed, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, and Baryshnikova, A

Subjects
1.1 Normal biological development and functioning, Proteins, Computational Biology, Molecular Sequence Annotation, knowledgebase, gene annotation, Databases, Gene Ontology Consortium, Gene Ontology, gene function, knowledge graphs, Genetic, Underpinning research, Genetics, Developmental Biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023

16. The Gene Ontology knowledgebase in 2023

Author

Consortium, Gene Ontology, Aleksander, Suzi A, Balhoff, James, Carbon, Seth, Cherry, J Michael, Drabkin, Harold J, Ebert, Dustin, Feuermann, Marc, Gaudet, Pascale, Harris, Nomi L, Hill, David P, Lee, Raymond, Mi, Huaiyu, Moxon, Sierra, Mungall, Christopher J, Muruganugan, Anushya, Mushayahama, Tremayne, Sternberg, Paul W, Thomas, Paul D, Van Auken, Kimberly, Ramsey, Jolene, Siegele, Deborah A, Chisholm, Rex L, Fey, Petra, Aspromonte, Maria Cristina, Nugnes, Maria Victoria, Quaglia, Federica, Tosatto, Silvio, Giglio, Michelle, Nadendla, Suvarna, Antonazzo, Giulia, Attrill, Helen, Dos Santos, Gil, Marygold, Steven, Strelets, Victor, Tabone, Christopher J, Thurmond, Jim, Zhou, Pinglei, Ahmed, Saadullah H, Asanitthong, Praoparn, Buitrago, Diana Luna, Erdol, Meltem N, Gage, Matthew C, Kadhum, Mohamed Ali, Li, Kan Yan Chloe, Long, Miao, Michalak, Aleksandra, Pesala, Angeline, Pritazahra, Armalya, Saverimuttu, Shirin CC, Su, Renzhi, Thurlow, Kate E, Lovering, Ruth C, Logie, Colin, Oliferenko, Snezhana, Blake, Judith, Christie, Karen, Corbani, Lori, Dolan, Mary E, Ni, Li, Sitnikov, Dmitry, Smith, Cynthia, Cuzick, Alayne, Seager, James, Cooper, Laurel, Elser, Justin, Jaiswal, Pankaj, Gupta, Parul, Naithani, Sushma, Lera-Ramirez, Manuel, Rutherford, Kim, Wood, Valerie, De Pons, Jeffrey L, Dwinell, Melinda R, Hayman, G Thomas, Kaldunski, Mary L, Kwitek, Anne E, Laulederkind, Stanley JF, Tutaj, Marek A, Vedi, Mahima, Wang, Shur-Jen, D'Eustachio, Peter, Aimo, Lucila, Axelsen, Kristian, Bridge, Alan, Hyka-Nouspikel, Nevila, Morgat, Anne, Engel, Stacia R, Karra, Kalpana, Miyasato, Stuart R, Nash, Robert S, Skrzypek, Marek S, Weng, Shuai, Wong, Edith D, Bakker, Erika, Berardini, Tanya Z, Reiser, Leonore, Auchincloss, Andrea, Argoud-Puy, Ghislaine, Blatter, Marie-Claude, Boutet, Emmanuel, Breuza, Lionel, Casals-Casas, Cristina, Coudert, Elisabeth, Estreicher, Anne, Famiglietti, Maria Livia, Gos, Arnaud, Gruaz-Gumowski, Nadine, Hulo, Chantal, Jungo, Florence, Le Mercier, Philippe, Lieberherr, Damien, Masson, Patrick, Pedruzzi, Ivo, Pourcel, Lucille, Poux, Sylvain, Rivoire, Catherine, Sundaram, Shyamala, Bateman, Alex, Bowler-Barnett, Emily, Bye-A-Jee, Hema, Denny, Paul, Ignatchenko, Alexandr, Ishtiaq, Rizwan, Lock, Antonia, Lussi, Yvonne, Magrane, Michele, Martin, Maria J, Orchard, Sandra, Raposo, Pedro, Speretta, Elena, Tyagi, Nidhi, Warner, Kate, Zaru, Rossana, Diehl, Alexander D, Chan, Juancarlos, Diamantakis, Stavros, Raciti, Daniela, Zarowiecki, Magdalena, Fisher, Malcolm, James-Zorn, Christina, Ponferrada, Virgilio, Zorn, Aaron, Ramachandran, Sridhar, Ruzicka, Leyla, and Westerfield, Monte

Subjects
Ecology,Evolution & Ethology, Cell Cycle & Chromosomes, Cell Biology
Abstract

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Published
2023
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22. The gene regulation knowledge commons: the action area of GREEKC

Author

Kuiper, Martin, Bonello, Joseph, Fernandez-Breis, Jesualdo T., Bucher, Philipp, Futschik, Matthias E., Gaudet, Pascale, Kulakovskiy, Ivan V., Licata, Luana, Logie, Colin, Lovering, Ruth C., Makeev, Vsevolod J., Orchard, Sandra, Panni, Simona, Perfetto, Livia, Sant, David, Schulz, Stefan, Vercruysse, Steven, Zerbino, Daniel R., Lægreid, Astrid, The GRECO Consortium, and The GRECO Consortium

Subjects
Computational biology, Text data mining, Ontology, Web services
Abstract

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC., peer-reviewed

Published
2022

24. The gene regulation knowledge commons: the action area of GREEKC

Author

Kuiper, Martin, primary, Bonello, Joseph, additional, Fernández-Breis, Jesualdo T., additional, Bucher, Philipp, additional, Futschik, Matthias E., additional, Gaudet, Pascale, additional, Kulakovskiy, Ivan V., additional, Licata, Luana, additional, Logie, Colin, additional, Lovering, Ruth C., additional, Makeev, Vsevolod J., additional, Orchard, Sandra, additional, Panni, Simona, additional, Perfetto, Livia, additional, Sant, David, additional, Schulz, Stefan, additional, Vercruysse, Steven, additional, Zerbino, Daniel R., additional, and Lægreid, Astrid, additional

Published
2022
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25. DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation

Author

Quaglia, Federica, primary, Mészáros, Bálint, additional, Salladini, Edoardo, additional, Hatos, András, additional, Pancsa, Rita, additional, Chemes, Lucía B, additional, Pajkos, Mátyás, additional, Lazar, Tamas, additional, Peña-Díaz, Samuel, additional, Santos, Jaime, additional, Ács, Veronika, additional, Farahi, Nazanin, additional, Fichó, Erzsébet, additional, Aspromonte, Maria Cristina, additional, Bassot, Claudio, additional, Chasapi, Anastasia, additional, Davey, Norman E, additional, Davidović, Radoslav, additional, Dobson, Laszlo, additional, Elofsson, Arne, additional, Erdős, Gábor, additional, Gaudet, Pascale, additional, Giglio, Michelle, additional, Glavina, Juliana, additional, Iserte, Javier, additional, Iglesias, Valentín, additional, Kálmán, Zsófia, additional, Lambrughi, Matteo, additional, Leonardi, Emanuela, additional, Longhi, Sonia, additional, Macedo-Ribeiro, Sandra, additional, Maiani, Emiliano, additional, Marchetti, Julia, additional, Marino-Buslje, Cristina, additional, Mészáros, Attila, additional, Monzon, Alexander Miguel, additional, Minervini, Giovanni, additional, Nadendla, Suvarna, additional, Nilsson, Juliet F, additional, Novotný, Marian, additional, Ouzounis, Christos A, additional, Palopoli, Nicolás, additional, Papaleo, Elena, additional, Pereira, Pedro José Barbosa, additional, Pozzati, Gabriele, additional, Promponas, Vasilis J, additional, Pujols, Jordi, additional, Rocha, Alma Carolina Sanchez, additional, Salas, Martin, additional, Sawicki, Luciana Rodriguez, additional, Schad, Eva, additional, Shenoy, Aditi, additional, Szaniszló, Tamás, additional, Tsirigos, Konstantinos D, additional, Veljkovic, Nevena, additional, Parisi, Gustavo, additional, Ventura, Salvador, additional, Dosztányi, Zsuzsanna, additional, Tompa, Peter, additional, Tosatto, Silvio C E, additional, and Piovesan, Damiano, additional

Published
2021
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27. A GO catalogue of human DNA-binding transcription factors

Author

Lovering, Ruth C., primary, Gaudet, Pascale, additional, Acencio, Marcio L., additional, Ignatchenko, Alex, additional, Jolma, Arttu, additional, Fornes, Oriol, additional, Kuiper, Martin, additional, Kulakovskiy, Ivan V., additional, Lægreid, Astrid, additional, Martin, Maria J., additional, and Logie, Colin, additional

Published
2021
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29. The gene regulation knowledge commons: the action area of GREEKC

Author

Kuiper, Martin, Bonello, Joseph, Fernández-Breis, Jesualdo T., Bucher, Philipp, Futschik, Matthias E., Gaudet, Pascale, Kulakovskiy, Ivan V., Licata, Luana, Logie, Colin, Lovering, Ruth C., Makeev, Vsevolod J., Orchard, Sandra, Panni, Simona, Perfetto, Livia, Sant, David, Schulz, Stefan, Vercruysse, Steven, Zerbino, Daniel R., Lægreid, Astrid, Vandepoele, Klaas, on behalf of the GRECO consortium, [ missing ], and GRECO Consortium

Subjects
Knowledge Commons, Knowledge management, Text mining, Process (engineering), PROTEINS, Biophysics, computer.software_genre, Biochemistry, Knowledge commons, Computational biology, Structural Biology, Political science, Genetics, Ontologies, Cost action, Molecular Biology, Web services, Regulation of gene expression, Settore BIO/18, business.industry, Biology and Life Sciences, Reproducibility of Results, DNA, BINDING SITES, Biocuration, ONTOLOGY, Workflow, Action (philosophy), Gene Expression Regulation, MOTIF, Web service, business, computer
Abstract

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various steps in the knowledge management process that focuses on understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to standardize and update existing knowledge management workflows and involve end-users in the process of designing the Gene Regulation Knowledge Commons (GRKC). Here the GREEKC consortium describes its main achievements in improving this GRKC. info:eu-repo/semantics/publishedVersion

Published
2021

32. A GO catalogue of human DNA-binding transcription factors

Author

Lovering, Ruth C., primary, Gaudet, Pascale, additional, Acencio, Marcio L., additional, Ignatchenko, Alex, additional, Jolma, Arttu, additional, Fornes, Oriol, additional, Kuiper, Martin, additional, Kulakovskiy, Ivan V., additional, Lægreid, Astrid, additional, Martin, Maria J., additional, and Logie, Colin, additional

Published
2020
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36. Towards BioDBcore: a community-defined information specification for biological databases

Author

Gaudet, Pascale, Bairoch, Amos, Field, Dawn, Sansone, Susanna-Assunta, Taylor, Chris, Attwood, Teresa K., Bateman, Alex, Blake, Judith A., Bult, Carol J., Cherry, J. Michael, Chisholm, Rex L., Cochrane, Guy, Cook, Charles E., Eppig, Janan T., Galperin, Michael Y., Gentleman, Robert, Goble, Carole A., Gojobori, Takashi, Hancock, John M., Howe, Douglas G., Imanishi, Tadashi, Kelso, Janet, Landsman, David, Lewis, Suzanna E., Mizrachi, Ilene Karsch, Orchard, Sandra, Ouellette, B. F. Francis, Ranganathan, Shoba, Richardson, Lorna, Rocca-Serra, Philippe, Schofield, Paul N., Smedley, Damian, Southan, Christopher, Tan, Tin Wee, Tatusova, Tatiana, Whetzel, Patricia L., White, Owen, and Yamasaki, Chisato

Published
2011
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37. The Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST)

Author

Touré, Vasundra, primary, Vercruysse, Steven, additional, Acencio, Marcio Luis, additional, Lovering, Ruth C, additional, Orchard, Sandra, additional, Bradley, Glyn, additional, Casals-Casas, Cristina, additional, Chaouiya, Claudine, additional, del-Toro, Noemi, additional, Flobak, Åsmund, additional, Gaudet, Pascale, additional, Hermjakob, Henning, additional, Hoyt, Charles Tapley, additional, Licata, Luana, additional, Lægreid, Astrid, additional, Mungall, Christopher J, additional, Niknejad, Anne, additional, Panni, Simona, additional, Perfetto, Livia, additional, Porras, Pablo, additional, Pratt, Dexter, additional, Saez-Rodriguez, Julio, additional, Thieffry, Denis, additional, Thomas, Paul D, additional, Türei, Dénes, additional, and Kuiper, Martin, additional

Published
2020
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38. Term Matrix: A novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns

Author

Wood, Valerie, primary, Carbon, Seth, additional, Harris, Midori A., additional, Lock, Antonia, additional, Engel, Stacia R., additional, Hill, David P., additional, Van Auken, Kimberly, additional, Attrill, Helen, additional, Feuermann, Marc, additional, Gaudet, Pascale, additional, Lovering, Ruth C., additional, Poux, Sylvain, additional, Rutherford, Kim M., additional, and Mungall, Christopher J., additional

Published
2020
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40. The neXtProt knowledgebase in 2020: data, tools and usability improvements

Author

Zahn-Zabal, Monique, primary, Michel, Pierre-André, additional, Gateau, Alain, additional, Nikitin, Frédéric, additional, Schaeffer, Mathieu, additional, Audot, Estelle, additional, Gaudet, Pascale, additional, Duek, Paula D, additional, Teixeira, Daniel, additional, Rech de Laval, Valentine, additional, Samarasinghe, Kasun, additional, Bairoch, Amos, additional, and Lane, Lydie, additional

Published
2019
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43. Annotation of gene product function from high-throughput studies using the Gene Ontology

Author

Attrill, Helen, Gaudet, Pascale, Huntley, Rachael P., Lovering, Ruth C., Engel, Stacia R., Poux, Sylvain, Van Auken, Kimberly M., Georghiou, George, Chibucos, Marcus C., Berardini, Tanya Z., Wood, Valerie, Drabkin, Harold, Fey, Petra, Garmiri, Penelope, Harris, Midori A., Sawford, Tony, Reiser, Leonore, Tauber, Rebecca, and Toro, Sabrina

Abstract

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community.

Published
2019

48. BioHackathon series in 2013 and 2014: improvements of semantic interoperability in life science data and services

Author

Katayama, Toshiaki, primary, Kawashima, Shuichi, additional, Micklem, Gos, additional, Kawano, Shin, additional, Kim, Jin-Dong, additional, Kocbek, Simon, additional, Okamoto, Shinobu, additional, Wang, Yue, additional, Wu, Hongyan, additional, Yamaguchi, Atsuko, additional, Yamamoto, Yasunori, additional, Antezana, Erick, additional, Aoki-Kinoshita, Kiyoko F., additional, Arakawa, Kazuharu, additional, Banno, Masaki, additional, Baran, Joachim, additional, Bolleman, Jerven T., additional, Bonnal, Raoul J. P., additional, Bono, Hidemasa, additional, Fernández-Breis, Jesualdo T., additional, Buels, Robert, additional, Campbell, Matthew P., additional, Chiba, Hirokazu, additional, Cock, Peter J. A., additional, Cohen, Kevin B., additional, Dumontier, Michel, additional, Fujisawa, Takatomo, additional, Fujiwara, Toyofumi, additional, Garcia, Leyla, additional, Gaudet, Pascale, additional, Hattori, Emi, additional, Hoehndorf, Robert, additional, Itaya, Kotone, additional, Ito, Maori, additional, Jamieson, Daniel, additional, Jupp, Simon, additional, Juty, Nick, additional, Kalderimis, Alex, additional, Kato, Fumihiro, additional, Kawaji, Hideya, additional, Kawashima, Takeshi, additional, Kinjo, Akira R., additional, Komiyama, Yusuke, additional, Kotera, Masaaki, additional, Kushida, Tatsuya, additional, Malone, James, additional, Matsubara, Masaaki, additional, Mizuno, Satoshi, additional, Mizutani, Sayaka, additional, Mori, Hiroshi, additional, Moriya, Yuki, additional, Murakami, Katsuhiko, additional, Nakazato, Takeru, additional, Nishide, Hiroyo, additional, Nishimura, Yosuke, additional, Ogishima, Soichi, additional, Ohta, Tazro, additional, Okuda, Shujiro, additional, Ono, Hiromasa, additional, Perez-Riverol, Yasset, additional, Shinmachi, Daisuke, additional, Splendiani, Andrea, additional, Strozzi, Francesco, additional, Suzuki, Shinya, additional, Takehara, Junichi, additional, Thompson, Mark, additional, Tokimatsu, Toshiaki, additional, Uchiyama, Ikuo, additional, Verspoor, Karin, additional, Wilkinson, Mark D., additional, Wimalaratne, Sarala, additional, Yamada, Issaku, additional, Yamamoto, Nozomi, additional, Yarimizu, Masayuki, additional, Kawamoto, Shoko, additional, and Takagi, Toshihisa, additional

Published
2019
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49. SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse

Author

Koopmans, Frank, primary, van Nierop, Pim, additional, Andres-Alonso, Maria, additional, Byrnes, Andrea, additional, Cijsouw, Tony, additional, Coba, Marcelo P., additional, Cornelisse, L. Niels, additional, Farrell, Ryan J., additional, Goldschmidt, Hana L., additional, Howrigan, Daniel P., additional, Hussain, Natasha K., additional, Imig, Cordelia, additional, de Jong, Arthur P.H., additional, Jung, Hwajin, additional, Kohansalnodehi, Mahdokht, additional, Kramarz, Barbara, additional, Lipstein, Noa, additional, Lovering, Ruth C., additional, MacGillavry, Harold, additional, Mariano, Vittoria, additional, Mi, Huaiyu, additional, Ninov, Momchil, additional, Osumi-Sutherland, David, additional, Pielot, Rainer, additional, Smalla, Karl-Heinz, additional, Tang, Haiming, additional, Tashman, Katherine, additional, Toonen, Ruud F.G., additional, Verpelli, Chiara, additional, Reig-Viader, Rita, additional, Watanabe, Kyoko, additional, van Weering, Jan, additional, Achsel, Tilmann, additional, Ashrafi, Ghazaleh, additional, Asi, Nimra, additional, Brown, Tyler C., additional, De Camilli, Pietro, additional, Feuermann, Marc, additional, Foulger, Rebecca E., additional, Gaudet, Pascale, additional, Joglekar, Anoushka, additional, Kanellopoulos, Alexandros, additional, Malenka, Robert, additional, Nicoll, Roger A., additional, Pulido, Camila, additional, de Juan-Sanz, Jaime, additional, Sheng, Morgan, additional, Südhof, Thomas C., additional, Tilgner, Hagen U., additional, Bagni, Claudia, additional, Bayés, Àlex, additional, Biederer, Thomas, additional, Brose, Nils, additional, Chua, John Jia En, additional, Dieterich, Daniela C., additional, Gundelfinger, Eckart D., additional, Hoogenraad, Casper, additional, Huganir, Richard L., additional, Jahn, Reinhard, additional, Kaeser, Pascal S., additional, Kim, Eunjoon, additional, Kreutz, Michael R., additional, McPherson, Peter S., additional, Neale, Ben M., additional, O’Connor, Vincent, additional, Posthuma, Danielle, additional, Ryan, Timothy A., additional, Sala, Carlo, additional, Feng, Guoping, additional, Hyman, Steven E., additional, Thomas, Paul D., additional, Smit, August B., additional, and Verhage, Matthijs, additional

Published
2019
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50. ECO, the Evidence & Conclusion Ontology: community standard for evidence information

Author

Giglio, Michelle, primary, Tauber, Rebecca, additional, Nadendla, Suvarna, additional, Munro, James, additional, Olley, Dustin, additional, Ball, Shoshannah, additional, Mitraka, Elvira, additional, Schriml, Lynn M, additional, Gaudet, Pascale, additional, Hobbs, Elizabeth T, additional, Erill, Ivan, additional, Siegele, Deborah A, additional, Hu, James C, additional, Mungall, Chris, additional, and Chibucos, Marcus C, additional

Published
2018
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