Literature DB >> 2684350

Methods for discovering novel motifs in nucleic acid sequences.

R Staden1.   

Abstract

We describe a computer tool to aid the discovery of new motifs in nucleic acid sequences. A typical use would be to analyse a set of upstream regions from a family of related genes in order to find possible control sequences. The heart of the method is the creation of dictionaries of related subsequences. These dictionaries can then be analysed to look for the commonest or best-defined subsequences, those that occur in the highest number of different sequences, or for those in equivalent positions within the family. We show the application of the method to a set of E. coli promoter sequences.

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Year:  1989        PMID： 2684350     DOI： 10.1093/bioinformatics/5.4.293

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


  18 in total

1.  GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

Authors:  J Besemer; A Lomsadze; M Borodovsky
Journal:  Nucleic Acids Res       Date:  2001-06-15       Impact factor: 16.971

2.  Protein and DNA requirements of the bacteriophage HP1 recombination system: a model for intasome formation.

Authors:  D Esposito; J S Thrower; J J Scocca
Journal:  Nucleic Acids Res       Date:  2001-10-01       Impact factor: 16.971

3.  A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles.

Authors:  Li-Wei Chang; Rakesh Nagarajan; Jeffrey A Magee; Jeffrey Milbrandt; Gary D Stormo
Journal:  Genome Res       Date:  2006-01-31       Impact factor: 9.043

4.  An efficient algorithm for identifying matches with errors in multiple long molecular sequences.

Authors:  M Y Leung; B E Blaisdell; C Burge; S Karlin
Journal:  J Mol Biol       Date:  1991-10-20       Impact factor: 5.469

5.  Computational identification and functional validation of regulatory motifs in cartilage-expressed genes.

Authors:  Sherri R Davies; Li-Wei Chang; Debabrata Patra; Xiaoyun Xing; Karen Posey; Jacqueline Hecht; Gary D Stormo; Linda J Sandell
Journal:  Genome Res       Date:  2007-09-04       Impact factor: 9.043

Review 6.  The Staden sequence analysis package.

Authors:  R Staden
Journal:  Mol Biotechnol       Date:  1996-06       Impact factor: 2.695

7.  Sequences attaching loops of nuclear and mitochondrial DNA to underlying structures in human cells: the role of transcription units.

Authors:  D A Jackson; J Bartlett; P R Cook
Journal:  Nucleic Acids Res       Date:  1996-04-01       Impact factor: 16.971

8.  Computational identification of cis-acting elements affecting post-transcriptional control of gene expression in Saccharomyces cerevisiae.

Authors:  J S Jacobs Anderson; R Parker
Journal:  Nucleic Acids Res       Date:  2000-04-01       Impact factor: 16.971

9.  Computational design and application of endogenous promoters for transcriptionally targeted gene therapy for rheumatoid arthritis.

Authors:  Jeroen Geurts; Leo A B Joosten; Nozomi Takahashi; Onno J Arntz; Anton Glück; Miranda B Bennink; Wim B van den Berg; Fons A J van de Loo
Journal:  Mol Ther       Date:  2009-08-18       Impact factor: 11.454

10.  Discovery of novel transcription factor binding sites by statistical overrepresentation.

Authors:  Saurabh Sinha; Martin Tompa
Journal:  Nucleic Acids Res       Date:  2002-12-15       Impact factor: 16.971
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