Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape
Abstract
An accurate characterization of transcription factor (TF)-DNA affinity landscape is crucial to a quantitative understanding of the molecular mechanisms underpinning endogenous gene regulation. While recent advances in biotechnology have brought the opportunity for building binding affinity prediction methods, the accurate characterization of TF-DNA binding affinity landscape still remains a challenging problem.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jul 27, 2017
- Source ID
- 10.1093/bioinformatics/btx480
Entities
People
- Hanjun Dai
- Hiroyuki Kuwahara
- Le Song
- Ramzan Umarov
- Xin Gao
- Yu Li
Organizations
- Georgia Tech
- King Abdullah University of Science and Technology
- National Institutes of Health
- National Science Foundation
- Office of Naval Research