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- Title
Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm.
- Authors
Ka-Chun Wong; Chengbin Peng; Man-Hon Wong; Kwong-Sak Leung
- Abstract
Protein-DNA bindings are essential activities. Understanding them forms the basis for further deciphering of biological and genetic systems. In particular, the protein-DNA bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) play a central role in gene transcription. Comprehensive TF-TFBS binding sequence pairs have been found in a recent study. However, they are in one-to-one mappings which cannot fully reflect the many-to-many mappings within the bindings. An evolutionary algorithm is proposed to learn generalized representations (many-to-many mappings) from the TF-TFBS binding sequence pairs (one-to-one mappings). The generalized pairs are shown to be more meaningful than the original TF-TFBS binding sequence pairs. Some representative examples have been analyzed in this study. In particular, it shows that the TF-TFBS binding sequence pairs are not presumably in one-to-one mappings. They can also exhibit many-to-many mappings. The proposed method can help us extract such many-to-many information from the one-to-one TF-TFBS binding sequence pairs found in the previous study, providing further knowledge in understanding the bindings between TFs and TFBSs.
- Subjects
DNA-protein interactions; COOPERATIVE binding (Biochemistry); NUCLEOTIDE sequence; TRANSCRIPTION factors; ALGORITHMS
- Publication
Soft Computing - A Fusion of Foundations, Methodologies & Applications, 2011, Vol 15, Issue 8, p1631
- ISSN
1432-7643
- Publication type
Article
- DOI
10.1007/s00500-011-0692-5