Protein Function Prediction: Problems and Pitfalls. Issue 1 (3rd September 2015)

• Record Type: Journal Article
• Authors: Pearson, William R.
• Editors: Bateman, Alex; Pearson, William R.; Stein, Lincoln D.; Stormo, Gary D.; Yates, John R.
• Is Part Of: Current protocols in bioinformatics. Volume 51:Issue 1(2015)
• Page Start: 4.12.1
• Page End: 4.12.8
• Publication Date: 2015-09-03
• Subjects: homology -- orthology -- paralogy -- function prediction -- gene ontology -- EC numbers; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/0471250953.bi0412s51
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: The characterization of new genomes based on their protein sets has been revolutionized by new sequencing technologies, but biologists seeking to exploit new sequence information are often frustrated by the challenges associated with accurately assigning biological functions to newly identified proteins. Here, we highlight some of the challenges in functional inference from sequence similarity. Investigators can improve the accuracy of function prediction by (1) being conservative about the evolutionary distance to a protein of known function; (2) considering the ambiguous meaning of "functional similarity, " and (3) being aware of the limitations of annotations in functional databases. Protein function prediction does not offer "one‐size‐fits‐all" solutions. Prediction strategies work better when the idiosyncrasies of function and functional annotation are better understood. © 2015 by John Wiley & Sons, Inc.