Literature DB >> 15905282

TAMO: a flexible, object-oriented framework for analyzing transcriptional regulation using DNA-sequence motifs.

D Benjamin Gordon1, Lena Nekludova, Scott McCallum, Ernest Fraenkel.   

Abstract

SUMMARY: TAMO (Tools for Analysis of MOtifs) is an object-oriented computational framework for interpreting transcriptional regulation using DNA-sequence motifs. To simplify the application of multiple motif discovery programs to genome-wide data, TAMO provides a sophisticated motif object with interfaces to several popular programs. In addition, TAMO provides modules for integrating motif analysis with diverse data sources including genomic sequences, microarrays and various databases. Finally, TAMO includes tools for sequence analysis, algorithms for scoring, comparing and clustering motifs, and several useful statistical tests. Recently, we have applied these tools to analyze tens of thousands of motifs derived from hundreds of microarray experiments.

Entities:  

Mesh：

Year:  2005        PMID： 15905282     DOI： 10.1093/bioinformatics/bti481

Source DB:  PubMed          Journal:  Bioinformatics        ISSN： 1367-4803            Impact factor:   6.937


  39 in total

1.  Sequentially acting Sox transcription factors in neural lineage development.

Authors:  Maria Bergsland; Daniel Ramsköld; Cécile Zaouter; Susanne Klum; Rickard Sandberg; Jonas Muhr
Journal:  Genes Dev       Date:  2011-11-15       Impact factor: 11.361

2.  A G-Box-Like Motif Is Necessary for Transcriptional Regulation by Circadian Pseudo-Response Regulators in Arabidopsis.

Authors:  Tiffany L Liu; Linsey Newton; Ming-Jung Liu; Shin-Han Shiu; Eva M Farré
Journal:  Plant Physiol       Date:  2015-11-19       Impact factor: 8.340

Review 3.  Applying whole-genome studies of epigenetic regulation to study human disease.

Authors:  J D Lieb; S Beck; M L Bulyk; P Farnham; N Hattori; S Henikoff; X S Liu; K Okumura; K Shiota; T Ushijima; J M Greally
Journal:  Cytogenet Genome Res       Date:  2006       Impact factor: 1.636

4.  W-ChIPMotifs: a web application tool for de novo motif discovery from ChIP-based high-throughput data.

Authors:  Victor X Jin; Jeff Apostolos; Naga Satya Venkateswara Ra Nagisetty; Peggy J Farnham
Journal:  Bioinformatics       Date:  2009-10-01       Impact factor: 6.937

5.  High-resolution transcription atlas of the mitotic cell cycle in budding yeast.

Authors:  Marina V Granovskaia; Lars J Jensen; Matthew E Ritchie; Joern Toedling; Ye Ning; Peer Bork; Wolfgang Huber; Lars M Steinmetz
Journal:  Genome Biol       Date:  2010-03-01       Impact factor: 13.583

6.  A data integration approach to mapping OCT4 gene regulatory networks operative in embryonic stem cells and embryonal carcinoma cells.

Authors:  Marc Jung; Hedi Peterson; Lukas Chavez; Pascal Kahlem; Hans Lehrach; Jaak Vilo; James Adjaye
Journal:  PLoS One       Date:  2010-05-21       Impact factor: 3.240

7.  Motif discovery in promoters of genes co-localized and co-expressed during myeloid cells differentiation.

Authors:  Alessandro Coppe; Francesco Ferrari; Andrea Bisognin; Gian Antonio Danieli; Sergio Ferrari; Silvio Bicciato; Stefania Bortoluzzi
Journal:  Nucleic Acids Res       Date:  2008-12-05       Impact factor: 16.971

8.  In silico identification of a core regulatory network of OCT4 in human embryonic stem cells using an integrated approach.

Authors:  Lukas Chavez; Abha S Bais; Martin Vingron; Hans Lehrach; James Adjaye; Ralf Herwig
Journal:  BMC Genomics       Date:  2009-07-15       Impact factor: 3.969

9.  Compo: composite motif discovery using discrete models.

Authors:  Geir Kjetil Sandve; Osman Abul; Finn Drabløs
Journal:  BMC Bioinformatics       Date:  2008-12-08       Impact factor: 3.169

10.  BRNI: Modular analysis of transcriptional regulatory programs.

Authors:  Iftach Nachman; Aviv Regev
Journal:  BMC Bioinformatics       Date:  2009-05-20       Impact factor: 3.169
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