1. Sequence‐based Detection of DNA‐binding Proteins using Multiple‐view Features Allied with Feature Selection.
- Author
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Zhou, Liling, Song, Xiaoning, Yu, Dong‐Jun, and Sun, Jun
- Subjects
DNA-binding proteins ,FEATURE selection ,GENETIC regulation ,FORECASTING ,STATISTICAL correlation ,DEOXYRIBOZYMES ,DNA - Abstract
DNA‐binding proteins play essential roles in many molecular functions and gene regulation. Therefore, it becomes highly desirable to develop effective computational techniques for detecting DNA‐binding proteins. In this paper, we proposed a new method, iDBP‐DEP, which performs DNA‐binding prediction by using the discriminative feature derived from multi‐view feature sources including evolutionary profile, dipeptide composition, and physicochemical properties with feature selection. We evaluated iDBP‐DEP on two benchmark datasets, i. e. PDB1075 and PDB594 by rigorous Jackknife test. Compared with the state‐of‐the‐art sequence‐based DNA‐binding predictors, the proposed iDBP‐DEP achieved 1.8 % and 3.0 % improvements of accuracy (Acc) and Mathew's Correlation Coefficient (MCC), respectively, on PDB1075 dataset; 7.4 % and 14.8 % improvements of Acc and MCC, respectively, on PDB594. The independent validation test with PDB186 show that the proposed method achieved the best performances on Acc (80.1 %) and MCC (0.684), which further demonstrated the robustness of iDBP‐DEP for the detection of DNA‐binding proteins. Datasets and codes used in this study are freely available at https://githup.com/Zll‐codeside/iDBP‐DEP. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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