標題: An integrated approach for genome-wide gene expression analysis
作者: Hu, YJ
資訊工程學系
Department of Computer Science
關鍵字: motifs;gene regulation;constructive induction;decision tree
公開日期: 1-Jun-2001
摘要: Since efficient and relatively cheap methods were developed for determining biosequences, a lot of biosequence data has been generated. As the main problem in molecular biology is the analysis of the data instead of the data acquisition, part of the study of computational biology is to extract all kinds of meaningful information from the sequences. Computer-assisted methods have become very important in analyzing biosequence data. However, most of the current computer-assisted methods are limited to Ending motifs. Genes can be regulated in many ways, including combinations of regulatory elements. This research is aimed at developing a new integrated system for genome-wide gene expression analysis. This research begins with a new motif-finding method, using a new objective function combining multiple well defined components and an improved stochastic iterative sampling strategy. Combinatorial motif analysis is accomplished by constructive induction that analyzes potential motif combinations. We then apply standard inductive learning algorithms to generate hypotheses for different gene behaviors. A genome-wide gene expression analysis demonstrated the value of this novel integrated system. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/S0169-2607(00)00126-7
http://hdl.handle.net/11536/29583
ISSN: 0169-2607
DOI: 10.1016/S0169-2607(00)00126-7
期刊: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Volume: 65
Issue: 3
起始頁: 163
結束頁: 174
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