Deep learning for inferring transcription factor binding sites
importance 6/10
ai assisted
Genomics and Chromatin Dynamics genomics stage: research
Problem
Identifying where transcription factors bind on DNA, which is difficult and costly to determine experimentally.
Why it matters
Transcription factor binding underpins understanding of gene regulation in health and disease.
What the AI did
Reviews deep learning models that predict transcription factor binding sites from DNA sequence, plus interpretability methods to reveal which features drive predictions.
Results
not stated in source
Impact
A review synthesizing advances; no new demonstrated result reported.
Record
| Venue | Current Opinion in Systems Biology |
|---|---|
| Published | 2020 |
| Work type | review |
| Authors | Peter K. Koo, Matt Ploenzke |
| Citations | 70 (OpenAlex, at import time) |
| References | 97 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1016/j.coisb.2020.04.001 |
| Open access | hybrid |
| Keywords | deep learning, transcription factor binding sites, genomics, interpretability, DNA sequence |
Importance rating
6
significant — thousands to millions affected
TF binding prediction underpins gene regulation understanding in health and disease; foundational biology, but this review reports no new results.