Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7533
Title: | Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm |
Authors: | Wong, Ka-Chun Peng, Chengbin Wong, Man-Hon Prof. LEUNG Kwong Sak |
Issue Date: | 2011 |
Source: | Soft Computing, 2011, vol. 15 ( 8) , pp. 1631 - 1642 |
Journal: | Soft Computing |
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. © 2011 Springer-Verlag |
Type: | Peer Reviewed Journal Article |
URI: | http://hdl.handle.net/20.500.11861/7533 |
ISSN: | 14337479 |
DOI: | 10.1007/s00500-011-0692-5 |
Appears in Collections: | Publication |
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