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Comparative analysis of regulatory motif discovery tools for transcription factor binding sites / 基因组蛋白质组与生物信息学报·英文版
Genomics, Proteomics & Bioinformatics ; (4): 131-142, 2007.
Article in English | WPRIM | ID: wpr-317017
ABSTRACT
In the post-genomic era, identification of specific regulatory motifs or transcription factor binding sites (TFBSs) in non-coding DNA sequences, which is essential to elucidate transcriptional regulatory networks, has emerged as an obstacle that frustrates many researchers. Consequently, numerous motif discovery tools and correlated databases have been applied to solving this problem. However, these existing methods, based on different computational algorithms, show diverse motif prediction efficiency in non-coding DNA sequences. Therefore, understanding the similarities and differences of computational algorithms and enriching the motif discovery literatures are important for users to choose the most appropriate one among the online available tools. Moreover, there still lacks credible criterion to assess motif discovery tools and instructions for researchers to choose the best according to their own projects. Thus integration of the related resources might be a good approach to improve accuracy of the application. Recent studies integrate regulatory motif discovery tools with experimental methods to offer a complementary approach for researchers, and also provide a much-needed model for current researches on transcriptional regulatory networks. Here we present a comparative analysis of regulatory motif discovery tools for TFBSs.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Protein Binding / Transcription Factors / Binding Sites / Algorithms / Molecular Sequence Data / Base Sequence / Sequence Homology, Nucleic Acid / Sequence Analysis, DNA / Computational Biology / Internet Type of study: Prognostic study Language: English Journal: Genomics, Proteomics & Bioinformatics Year: 2007 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Protein Binding / Transcription Factors / Binding Sites / Algorithms / Molecular Sequence Data / Base Sequence / Sequence Homology, Nucleic Acid / Sequence Analysis, DNA / Computational Biology / Internet Type of study: Prognostic study Language: English Journal: Genomics, Proteomics & Bioinformatics Year: 2007 Type: Article