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CIBCB
2006
IEEE

A Systematic Computational Approach for Transcription Factor Target Gene Prediction

11 years 5 months ago
A Systematic Computational Approach for Transcription Factor Target Gene Prediction
— Computational prediction of transcription factor’s binding sites and regulatory target genes has great value to the biological studies of cellular process. Existing practices either look into first-hand gene expression data which could be costly for large scale analysis, or apply statistical or heuristic learning methods to discover potential binding sites which have limited accuracy due to the complexity of the data. Based on wellstudied information retrieval theories, this paper proposes a novel systematic approach for transcription factor target gene prediction. The key of the approach is to model the prediction problem as a classification task by representing the features of the sequential data into vector data points in a higher-order domain. The proposed approach has produced satisfactory results in our controlled experiment on Auxin Response Factor (ARF) target gene prediction in Arabidopsis.
Ji He, Xinbin Dai, Xuechun Zhao
Added 10 Jun 2010
Updated 10 Jun 2010
Type Conference
Year 2006
Where CIBCB
Authors Ji He, Xinbin Dai, Xuechun Zhao
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