The Gene Ontology knowledgebase in 2023
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 knowl...
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| Vydané v: | Genetics (Austin) Ročník 224; číslo 1 |
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| Hlavní autori: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
US
Oxford University Press
04.05.2023
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| ISSN: | 1943-2631, 1943-2631 |
| On-line prístup: | Získať plný text |
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| Abstract | 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. |
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| AbstractList | 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. 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.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. 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. |
| Author | Vedi, Mahima Hulo, Chantal Elser, Justin Aleksander, Suzi A Ahmed, Saadullah H Luna Buitrago, Diana Ignatchenko, Alexandr Ishtiaq, Rizwan Rivoire, Catherine Warner, Kate Fisher, Malcolm Axelsen, Kristian Dolan, Mary E Ebert, Dustin Harris, Nomi L Ponferrada, Virgilio Poux, Sylvain Lera-Ramirez, Manuel Long, Miao Engel, Stacia R Lock, Antonia Diamantakis, Stavros Thurmond, Jim Lussi, Yvonne Giglio, Michelle Zhou, Pinglei Moxon, Sierra Magrane, Michele Cherry, J Michael Martin, Maria J Antonazzo, Giulia Argoud-Puy, Ghislaine Masson, Patrick Carbon, Seth Hill, David P Logie, Colin Mi, Huaiyu Nash, Robert S Auchincloss, Andrea Tosatto, Silvio Berardini, Tanya Z Mushayahama, Tremayne Smith, Cynthia Zorn, Aaron Aimo, Lucila Speretta, Elena Corbani, Lori Pourcel, Lucille Tabone, Christopher J Kwitek, Anne E Bowler-Barnett, Emily Kaldunski, Mary L Wong, Edith D Ali Kadhum, Mohamed Weng, Shuai Bateman, Alex Gruaz-Gumowski, Nadine Naithani, Sushma Pesala, Angeline Lieberherr, Damien Lee, Raymond Siegele, Deborah A Cooper, Laurel Tyagi, Nidhi Cuzick, Alayne By |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36866529$$D View this record in MEDLINE/PubMed |
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| Contributor | Ramsey, Jolene Pritazahra, Armalya Vedi, Mahima Elser, Justin Fey, Petra Oliferenko, Snezhana Aleksander, Suzi A Ahmed, Saadullah H Luna Buitrago, Diana Drabkin, Harold J Chisholm, Rex L Strelets, Victor Axelsen, Kristian Dolan, Mary E Ni, Li Ebert, Dustin Harris, Nomi L Nadendla, Suvarna Blake, Judith Jaiswal, Pankaj Lera-Ramirez, Manuel Thomas, Paul D Hyka-Nouspikel, Nevila Long, Miao Engel, Stacia R Wood, Valerie Thurmond, Jim D'Eustachio, Peter Giglio, Michelle Zhou, Pinglei Moxon, Sierra Skrzypek, Marek S Seager, James Cherry, J Michael Aspromonte, Maria Cristina Antonazzo, Giulia Saverimuttu, Shirin C C Attrill, Helen Carbon, Seth Hill, David P Christie, Karen Logie, Colin Feuermann, Marc Mi, Huaiyu Nash, Robert S Tosatto, Silvio Berardini, Tanya Z Mushayahama, Tremayne Smith, Cynthia Miyasato, Stuart R Aimo, Lucila Laulederkind, Stanley J F Corbani, Lori Quaglia, Federica Balhoff, James Morgat, Anne Marygold, Steven Su, Renzhi Michalak, Aleksandra Asanitthong, Praoparn Wang, Shur-Jen Muruganugan, Anushya Sternberg, Paul W Tabone, Christophe |
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| Copyright | The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America. 2023 The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America. |
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| Keywords | gene function gene annotation knowledge graphs knowledgebase Gene Ontology |
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The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products... The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and... |
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| SubjectTerms | Computational Biology Databases, Genetic Gene Ontology Molecular Sequence Annotation Proteins - genetics |
| Title | The Gene Ontology knowledgebase in 2023 |
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