Identification of regulatory relationships between transcription factors (TFs) and their targets is a central problem in post-genomic biology. In this paper, we apply an approach based on the support vector machine (SVM) and gene-expression data to predict the regulatory interactions in Arabidopsis.
A computational method of predicting regulatory interactions in Arabidopsis based on gene expression data and sequence information
β Scribed by Yu, Xiaoqing; Gao, Hongyun; Zheng, Xiaoqi; Li, Chun; Wang, Jun
- Book ID
- 122928231
- Publisher
- Elsevier Science
- Year
- 2014
- Tongue
- English
- Weight
- 170 KB
- Volume
- 51
- Category
- Article
- ISSN
- 1476-9271
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