Accurate and efficient gene function prediction using a multi-bacterial network
Abstract
Nearly 40% of the genes in sequenced genomes have no experimentally or computationally derived functional annotations. To fill this gap, we seek to develop methods for network-based gene function prediction that can integrate heterogeneous data for multiple species with experimentally based functional annotations and systematically transfer them to newly sequenced organisms on a genome-wide scale. However, the large sizes of such networks pose a challenge for the scalability of current methods.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 16, 2020
- Source ID
- 10.1093/bioinformatics/btaa885
Entities
People
- Jeffrey N Law
- Shiv D. Kale
- T M Murali
Organizations
- Army Research Office
- Federal Government of the United States
- Intelligence Advanced Research Projects Activity
- National Science Foundation
- Office of the Director of National Intelligence
- Virginia Tech