The Gene Ontology Handbook

@inproceedings{Dessimoz2017TheGO,
  title={The Gene Ontology Handbook},
  author={C. Dessimoz and N. Skunca},
  booktitle={Methods in Molecular Biology},
  year={2017}
}
As molecular biology has increasingly become a data-intensive discipline, ontologies have emerged as an essential computational tool to assist in the organisation, description and analysis of data. Ontologies describe and classify the entities of interest in a scientifi c domain in a computationally accessible fashion such that algorithms and tools can be developed around them. The technology that underlies ontologies has its roots in logic-based artifi cial intelligence, allowing for… Expand

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References

SHOWING 1-10 OF 57 REFERENCES
Primer on the Gene Ontology.
TLDR
This chapter provides a concise primer for all users of the Gene Ontology, briefly introducing the structure of the ontology and explaining how to interpret annotations associated with the GO. Expand
Gene Ontology: tool for the unification of biology
TLDR
The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. Expand
The Gene Ontology and the Meaning of Biological Function.
  • P. Thomas
  • Computer Science, Medicine
  • Methods in molecular biology
  • 2017
TLDR
An explicit formulation of the biological model that underlies the GO and annotations is presented, and how this model relates to the broader debates on the meaning of biological function is discussed. Expand
Semantic Similarity in Biomedical Ontologies
TLDR
This work reviews semantic similarity measures applied to biomedical ontologies and proposes their classification according to the strategies they employ: node-based versus edge-based and pairwise versus groupwise. Expand
Measuring semantic similarity between Gene Ontology terms
TLDR
GraSM, a novel method that uses all the information in the graph structure of the Gene Ontology, instead of considering it as a hierarchical tree, gives a consistently higher family similarity correlation on all aspects of GO than the original semantic similarity measures. Expand
The Confidence Information Ontology: a step towards a standard for asserting confidence in annotations
TLDR
This work presents the elements that were identified as essential for assessing confidence in annotations, as well as a draft ontology—the Confidence Information Ontology—to illustrate how the problems identified could be addressed. Expand
Community-Wide Evaluation of Computational Function Prediction.
TLDR
The rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge involving a broad scientific community according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms are discussed. Expand
Quality of Computationally Inferred Gene Ontology Annotations
TLDR
Overall, it is found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. Expand
Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms
TLDR
The entire engine has been completely rewritten to improve both accuracy and computational efficiency, thus allowing for the annotation of complete genomes. Expand
The InterPro protein families database: the classification resource after 15 years
TLDR
The new domain architecture search tool is described and the process of mapping of Gene Ontology terms to InterPro is outlined, and the challenges faced by the resource given the explosive growth in sequence data in recent years are discussed. Expand
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