Use and misuse of the gene ontology annotations

By Seung Yon Rhee, V. Wood, Kara Dolinski, Sorin Draghici. 2008

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Citations in the corpus

Re-thinking organisms: The impact of databases on model organism biology. (2012, background): “Well aware of the epistemic power of their classification systems, database curators continue to campaign to raise awareness among biologists of how bio-ontologies are built and how experimenters can contribute to that process (Garcia-Hernandez and Reiser 2006; Rhee et al. 2008).”
The Human Phenotype Ontology (2010, methodology): “Although the GO was originally developed primarily to provide a means for integration, retrieval, and computation of data (33), it is now commonly used to help understand the results of high-throughput expression profiling experiments (34), as well as for network modeling (35), analysis of semantic ”
Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges (2012, background): “Annotations inferred from indirect evidence are considered to be of lower quality than those derived from direct experimental evidence, although this opinion has not been shown robustly [54].”
Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists (2008, unknown): “It is not uncommon for users to try multiple tools with similar analytic capability for the same dataset in order to obtain maximum satisfactory analytic results (75).”
Mining breast cancer genes with a network based noise-tolerant approach (2013, background): “However, not all GO annotations are equally credible [34].”
Gene Ontology: Pitfalls, Biases, and Remedies. (2016, methodology): “Instead, one should use zebrafish gene-related annotations only as background (15).”
Evolution of Gene Duplication in Plants1[OPEN] (2016, background): “Although GO-based analysis has been informative, there can be significant issues with its use (Rhee et al., 2008), particularly because there are differences in the quality of functional annotation for different genomes.”
agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update (2017, background): “Relatively more comprehensive and accurate versions are being produced based on the evidence codes and/or comparative genomics to reduce the substantial number of false positives (20).”
Primer on the Gene Ontology (2016, methodology): “One common use is to infer commonalities in the location or function of genes that are over- or under-expressed (4, 6) [+cross-reference to Sebastian Bauer’s chapter].”
The Gene Ontology's Reference Genome Project: A Unified Framework for Functional Annotation across Species (2009, methodology): “org) to 27,029 in Arabidopsis thaliana [5], for a total of roughly 200,000 genes.”
From brain maps to cognitive ontologies: informatics and the search for mental structure (2015, background): “Most important, it has provided the ability to assess, for any specific set of genes, which entities in the ontology are likely to be “enriched” for that set of genes, thus providing insights into the larger biological context for the experiment (Rhee et al. 2008).”