Reference: Benso A, et al. (2013) A combined approach for genome wide protein function annotation/prediction. Proteome Sci 11(Suppl 1):S1

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Abstract


Background: Today large scale genome sequencing technologies are uncovering an increasing amount of new genes and proteins, which remain uncharacterized. Experimental procedures for protein function prediction are low throughput by nature and thus can't be used to keep up with the rate at which new proteins are discovered. On the other hand, proteins are the prominent stakeholders in almost all biological processes, and therefore the need to precisely know their functions for a better understanding of the underlying biological mechanism is inevitable. The challenge of annotating uncharacterized proteins in functional genomics and biology in general motivates the use of computational techniques well orchestrated to accurately predict their functions.

Methods: We propose a computational flow for the functional annotation of a protein able to assign the most probable functions to a protein by aggregating heterogeneous information. Considered information include: protein motifs, protein sequence similarity, and protein homology data gathered from interacting proteins, combined with data from highly similar non-interacting proteins (hereinafter called Similactors). Moreover, to increase the predictive power of our model we also compute and integrate term specific relationships among functional terms based on Gene Ontology (GO).

Results: We tested our method on Saccharomyces Cerevisiae and Homo sapiens species proteins. The aggregation of different structural and functional evidence with GO relationships outperforms, in terms of precision and accuracy of prediction than the other methods reported in literature. The predicted precision and accuracy is 100% for more than half of the input set for both species; overall, we obtained 85.38% precision and 81.95% accuracy for Homo sapiens and 79.73% precision and 80.06% accuracy for Saccharomyces Cerevisiae species proteins.

Reference Type
Journal Article
Authors
Benso A, Di Carlo S, Ur Rehman H, Politano G, Savino A, Suravajhala P
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Gene Ontology Annotations


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Gene/Complex Qualifier Gene Ontology Term Aspect Annotation Extension Evidence Method Source Assigned On Reference

Phenotype Annotations


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Gene Phenotype Experiment Type Mutant Information Strain Background Chemical Details Reference

Disease Annotations


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Gene Disease Ontology Term Qualifier Evidence Method Source Assigned On Reference

Regulation Annotations


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Regulator Target Direction Regulation Of Happens During Method Evidence

Post-translational Modifications


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Site Modification Modifier Reference

Interaction Annotations


Genetic Interactions

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Interactor Interactor Allele Assay Annotation Action Phenotype SGA score P-value Source Reference

Physical Interactions

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Interactor Interactor Assay Annotation Action Modification Source Reference

Functional Complementation Annotations


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Gene Species Gene ID Strain background Direction Details Source Reference