HTAD: a human-in-the-loop framework for supervised chromatin domain detection
Wei Shen, Ping Zhang, Yiwei Jiang, Hailin Tao, Zhike Zi, Li Li · 2024
Read HTAD: a human-in-the-loop framework for supervised chromatin domain detection by Wei Shen, Ping Zhang, Yiwei Jiang, Hailin Tao, Zhike Zi, Li Li (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11610164.txt.
Description
Shen and co-authors present HTAD, a tool that finds chromatin domains with human help. These domains, called TADs, are core units of genome folding that shape gene control and disease risk. Automated finders struggle with noisy backgrounds and domains nested inside larger domains.
HTAD mixes machine learning with expert guidance to raise accuracy. It first extracts features for candidate border pairs in the genome. An active learning loop then asks humans to label the most useful cases, refining the model step by step. The result is a supervised caller that learns from both data and expert judgment.
Catalog record
| CREATOR | Wei Shen, Ping Zhang, Yiwei Jiang, Hailin Tao, Zhike Zi, Li Li |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |