Computational Methods for Annotation Transfers from Sequence

Methods Mol Biol. 2017:1446:55-67. doi: 10.1007/978-1-4939-3743-1_5.

Abstract

Surveys of public sequence resources show that experimentally supported functional information is still completely missing for a considerable fraction of known proteins and is clearly incomplete for an even larger portion. Bioinformatics methods have long made use of very diverse data sources alone or in combination to predict protein function, with the understanding that different data types help elucidate complementary biological roles. This chapter focuses on methods accepting amino acid sequences as input and producing GO term assignments directly as outputs; the relevant biological and computational concepts are presented along with the advantages and limitations of individual approaches.

Keywords: De novo function prediction; Homology-based annotation transfers; Multi-domain architecture; Phylogenomics; Protein function prediction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Databases, Protein
  • Gene Ontology*
  • Humans
  • Molecular Sequence Annotation / methods*
  • Phylogeny
  • Proteins / genetics
  • Proteins / metabolism

Substances

  • Proteins