DconnLoop: a deep learning model for predicting chromatin loops based on multi-source data integration
The results demonstrate that DconnLoop outperforms existing methods in both precision and recall. In various experiments, including Aggregate Peak Analysis and peak enrichment comparisons, DconnLoop consistently shows advantages. Extensive ablation studies and validation across different sequencing depths further confirm DconnLoop's robustness and generalizability.
Authors
- Huimin Luo (ORCID: https://orcid.org/0000-0002-5066-5372)
- Ke‐Sheng Cheng (ORCID: https://orcid.org/0000-0001-8026-0053)
- Junfeng Wang (ORCID: https://orcid.org/0000-0003-2756-8803)
- Junwei Luo (ORCID: https://orcid.org/0000-0001-6841-9893)
- Chaokun Yan (ORCID: https://orcid.org/0000-0002-6246-7242)
Institutions
- Henan University (CN)
- Henan Polytechnic University (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1186/s12859-025-06092-6
- Citations
- 5
- Primary Topic
- Genomics and Chromatin Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 4.03