Literature DB >> 8996789

GenomeInspector: a new approach to detect correlation patterns of elements on genomic sequences.

K Quandt1, K Grote, T Werner.   

Abstract

MOTIVATION: Most of the sequences determined in current genome sequencing projects remain at least partially unannotated. The available software for DNA sequence analysis is usually limited to the prediction of individual elements (level 1 methods), but does not assess the context of different motifs. However, the functionality of biological units like promoters depends on the correct spatial organization of multiple individual elements.
RESULTS: Here, we present a second-level software package called GenomeInspector [[http:@www.gsf.de/biodv/genomeinspector.html ]], for further analysis of results obtained with level 1 methods (e.g. MatInspector [[http:@www.gsf.de/biodv/matinspector.html ]] or ConsInspector [[http:@www.gsf.de/biodv/consinspector.html++ +]]). One of the main features of this modular program is its ability to assess distance correlations between large sets of sequence elements which can be used for the identification and definition of basic patterns of functional units. The program provides an easy-to-use graphical user interface with direct comprehensive display of all results for megabase sequences. Sequence elements showing spatial correlations can be easily extracted and traced back to the nucleotide sequence with the program. GenomeInspector identified promoters of glycolytic enzymes in yeast [[http:@www.mips.biochem.mpg.de/mips/yeast/]] as members of a subgroup with unusual location of an ABF1 site. Solely on the basis of distance correlation analysis, the program correctly selected those transcription factors within these promoters already known to be involved in the regulation of glycolytic enzymes, demonstrating the power of this method.

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Year:  1996        PMID: 8996789     DOI: 10.1093/bioinformatics/12.5.405

Source DB:  PubMed          Journal:  Comput Appl Biosci        ISSN: 0266-7061


  9 in total

1.  Discovering regulatory elements in non-coding sequences by analysis of spaced dyads.

Authors:  J van Helden; A F Rios; J Collado-Vides
Journal:  Nucleic Acids Res       Date:  2000-04-15       Impact factor: 16.971

2.  Integrated functional and bioinformatics approach for the identification and experimental verification of RNA signals: application to HIV-1 INS.

Authors:  Horst Wolff; Ruth Brack-Werner; Markus Neumann; Thomas Werner; Ralf Schneider
Journal:  Nucleic Acids Res       Date:  2003-06-01       Impact factor: 16.971

3.  A motif co-occurrence approach for genome-wide prediction of transcription-factor-binding sites in Escherichia coli.

Authors:  Martha L Bulyk; Abigail M McGuire; Nobuhisa Masuda; George M Church
Journal:  Genome Res       Date:  2004-02       Impact factor: 9.043

4.  Recent computational approaches to understand gene regulation: mining gene regulation in silico.

Authors:  I Abnizova; T Subhankulova; Wr Gilks
Journal:  Curr Genomics       Date:  2007-04       Impact factor: 2.236

5.  Transcription factor map alignment of promoter regions.

Authors:  Enrique Blanco; Xavier Messeguer; Temple F Smith; Roderic Guigó
Journal:  PLoS Comput Biol       Date:  2006-05-26       Impact factor: 4.475

6.  Computational technique for improvement of the position-weight matrices for the DNA/protein binding sites.

Authors:  Naum I Gershenzon; Gary D Stormo; Ilya P Ioshikhes
Journal:  Nucleic Acids Res       Date:  2005-04-22       Impact factor: 16.971

7.  ColoWeb: a resource for analysis of colocalization of genomic features.

Authors:  RyangGuk Kim; Owen K Smith; Wing Chung Wong; Alex M Ryan; Michael C Ryan; Mirit I Aladjem
Journal:  BMC Genomics       Date:  2015-02-28       Impact factor: 3.969

8.  Optimizing the GATA-3 position weight matrix to improve the identification of novel binding sites.

Authors:  Soumyadeep Nandi; Ilya Ioshikhes
Journal:  BMC Genomics       Date:  2012-08-22       Impact factor: 3.969

9.  Identification of cis-regulatory modules in promoters of human genes exploiting mutual positioning of transcription factors.

Authors:  Soumyadeep Nandi; Alexandre Blais; Ilya Ioshikhes
Journal:  Nucleic Acids Res       Date:  2013-08-02       Impact factor: 16.971

  9 in total

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