Abstract
Protein-DNA interactions are involved in different cancer pathways. In particular, the DNA-binding domains of proteins can determine where and how gene regulatory regions are bound in different cell lines at different stages. Therefore, it is essential to develop a method to predict and locate the core residues on cancer-related DNA-binding domains. In this study, we propose a computational method to predict and locate core residues on DNA-binding domains. In particular, we have selected the cancer-related DNA-binding domains for in-depth studies, namely, winged Helix Turn Helix family, homeodomain family, and basic Helix-Loop-Helix family. The results demonstrate that the proposed method can predict the core residues involved in protein-DNA interactions, as verified by the existing structural data. Given its good performance, various aspects of the method are discussed and explored: for instance, different uses of prediction algorithm, different protein domains, and hotspot threshold setting.
| Original language | English |
|---|---|
| Pages (from-to) | 1-7 |
| Journal | Cancer Informatics |
| Volume | 15 |
| DOIs | |
| Publication status | Published - 2 Jun 2016 |
Research Keywords
- Applied machine learning
- Big data analytics
- Bioinformatics
- Cancer
- DNA-binding domains
- Protein-DNA binding interactions
- SNPdryad
Publisher's Copyright Statement
- This full text is made available under CC-BY-NC 3.0. https://creativecommons.org/licenses/by-nc/3.0/