Phylo-PFP: improved automated protein function prediction using phylogenetic distance of distantly related sequences
Abstract
Function annotation of proteins is fundamental in contemporary biology across fields including genomics, molecular biology, biochemistry, systems biology and bioinformatics. Function prediction is indispensable in providing clues for interpreting omics-scale data as well as in assisting biologists to build hypotheses for designing experiments. As sequencing genomes is now routine due to the rapid advancement of sequencing technologies, computational protein function prediction methods have become increasingly important. A conventional method of annotating a protein sequence is to transfer functions from top hits of a homology search; however, this approach has substantial short comings including a low coverage in genome annotation.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Aug 25, 2018
- Source ID
- 10.1093/bioinformatics/bty704
Entities
People
- Aashish Jain
- Daisuke Kihara
Organizations
- Army Research Office
- Intelligence Advanced Research Projects Activity
- National Institutes of Health
- National Science Foundation
- Office of the Director of National Intelligence
- Purdue University