Gene Ontology: tool for the unification of biology

By Michael Ashburner, C. Ball, Judith A. Blake, David Botstein, Heather Butler, J. Cherry, Allan Peter Davis, Kara Dolinski, S. Dwight, Janan T. Eppig and 10 more. 2000

42,547 citations recorded by the source corpus.

Subfields: Molecular Biology, Knowledge Graphs & Representation, Computational Biology & Bioinformatics

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Citations in the corpus

Constructing Datasets for Multi-hop Reading Comprehension Across Documents (2017, background): “There are a plethora of manually curated structured resources (Ashburner et al., 2000; The UniProt Consortium, 2017) which can either serve as ground truth or to induce training data using distant supervision (Craven and Kumlien, 1999; Bobic et al., 2012).”
Strategies for Pre-training Graph Neural Networks (2019, methodology): “We deﬁne ﬁne-grained protein functions as Gene Ontology (GO) annotations that are leaves in the GO hierarchy, and deﬁne coarse-grained protein functions as GO annotations that are the immediate parents of leaves (Ashburner et al., 2000; Consortium, 2018).”
Knowledge Graph Embedding by Translating on Hyperplanes (2014, background): “Knowledge graphs such as Freebase (Bollacker et al. 2008), WordNet (Miller 1995) and GeneOntology (Ashburner et al. 2000) have become very important resources to support many AI related applications, such as web/mobile search, Q&A, etc.”
ProGen: Language Modeling for Protein Generation (2020, methodology): “Following the definitions laid out in the UniprotKB controlled, hierarchical vocabulary of keywords (many of which are derived from Gene Ontology (GO) terms) [5], the conditioning keyword tags included 1100 terms ranging from cellular component, biological process, and molecular function terms.”
UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches (2014, methodology): “unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. atics/article-abstract/31/6/926/214968 by TEL AVIV U N IVER SITY user on 22 Septem ber 2019 summary cluster and membership information, including the sequence of a representative…”
CATH: an expanded resource to predict protein function through structure and sequence (2016, background): “Gene Ontology (GO) (12) and EC classification (13) terms), this constitutes 27 459 unique functional terms associated with FunFam sequences (4504 different EC terms and 22 955 different GO terms).”
Community detection in graphs (2009, background): “A community is considered biologically homogeneous if the functional similarity between protein pairs of the community (extracted through the Gene Ontology database (Ashburner et al., 2000)) is larger than the functional similarity between all protein pairs of the network.”
Cytoscape: a software environment for integrated models of biomolecular interaction networks. (2003, background): “Annotations typically correspond to an existing repository of knowledge, such as the Gene Ontology database (2).”
Uncovering disease-disease relationships through the incomplete human interactome (2015, positive): “For the analysis of the similarity between genes and diseases, we use (i) Gene Ontology (GO) annotations (49); (ii) tissue-specific gene expression data (36); (iii) symptom disease associations (38); (iv) comorbidity data (39); and (v) pathway annotations from theMolecular Signatures Database (MSigD”
The Edinburgh human metabolic network reconstruction and its functional analysis (2007, methodology): “We are working on it to develop a GO (Gene Ontology) (Ashburner et al , 2000)-based hierarchically compartmented human network for the next release.”