Literature DB >> 11471240

Muscle actin genes: a first step towards computational classification of tissue specific promoters.

K Frech1, K Quandt, T Werner.   

Abstract

Tissue-specific gene expression is governed by enhancer and promoter sequences determining the specificity most probably by their internal organization of transcription factor binding sites. In case of muscle-specific gene expression excellent compilations of sequence regions responsible for the tissue-specificity are available. We took advantage of such a compilation in order to elucidate organizational features that are directly correlated with promoter specificity. We chose a systematic approach solely based on a sequence collection known to consist of specific regulatory regions which can in principle be applied to every precompiled set of such sequences. We were able to show that these sequences contained a detectable subgroup (actin promoters) for which it was possible to construct a highly specific promoter model recognizing the majority of all known actin sequences. The model was robust with respect to different training sets, almost 100% specific and sensitive enough to be suitable for database searches. We believe this pilot study demonstrates the general applicability of our approach as well as the concept of modular promoter organization.

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Year:  1998        PMID: 11471240

Source DB:  PubMed          Journal:  In Silico Biol        ISSN: 1386-6338


  11 in total

1.  First pass annotation of promoters on human chromosome 22.

Authors:  M Scherf; A Klingenhoff; K Frech; K Quandt; R Schneider; K Grote; M Frisch; V Gailus-Durner; A Seidel; R Brack-Werner; T Werner
Journal:  Genome Res       Date:  2001-03       Impact factor: 9.043

2.  In silico prediction of scaffold/matrix attachment regions in large genomic sequences.

Authors:  Matthias Frisch; Kornelie Frech; Andreas Klingenhoff; Kerstin Cartharius; Ines Liebich; Thomas Werner
Journal:  Genome Res       Date:  2002-02       Impact factor: 9.043

3.  An approach to identify over-represented cis-elements in related sequences.

Authors:  Jiashun Zheng; Jiajin Wu; Zhirong Sun
Journal:  Nucleic Acids Res       Date:  2003-04-01       Impact factor: 16.971

4.  Genome-wide in silico identification of transcriptional regulators controlling the cell cycle in human cells.

Authors:  Ran Elkon; Chaim Linhart; Roded Sharan; Ron Shamir; Yosef Shiloh
Journal:  Genome Res       Date:  2003-05       Impact factor: 9.043

5.  Discovering functional transcription-factor combinations in the human cell cycle.

Authors:  Zhou Zhu; Jay Shendure; George M Church
Journal:  Genome Res       Date:  2005-06       Impact factor: 9.043

6.  TiProD: the Tissue-specific Promoter Database.

Authors:  Xin Chen; Jian-min Wu; Klaus Hornischer; Alexander Kel; Edgar Wingender
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

7.  Composite Module Analyst: identification of transcription factor binding site combinations using genetic algorithm.

Authors:  T Waleev; D Shtokalo; T Konovalova; N Voss; E Cheremushkin; P Stegmaier; O Kel-Margoulis; E Wingender; A Kel
Journal:  Nucleic Acids Res       Date:  2006-07-01       Impact factor: 16.971

8.  Beyond microarrays: find key transcription factors controlling signal transduction pathways.

Authors:  Alexdander Kel; Nico Voss; Ruy Jauregui; Olga Kel-Margoulis; Edgar Wingender
Journal:  BMC Bioinformatics       Date:  2006-09-06       Impact factor: 3.169

9.  Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining.

Authors:  Xochitl C Morgan; Shulin Ni; Daniel P Miranker; Vishwanath R Iyer
Journal:  BMC Bioinformatics       Date:  2007-11-15       Impact factor: 3.169

10.  Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

Authors:  Alexander E Kel; Monika Niehof; Volker Matys; Rüdiger Zemlin; Jürgen Borlak
Journal:  Genome Biol       Date:  2008-02-21       Impact factor: 13.583

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