Literature DB >> 18354784

Transcription factor functionality and transcription regulatory networks.

Christian A Grove1, Albertha J M Walhout.   

Abstract

Now that numerous high-quality complete genome sequences are available, many efforts are focusing on the "second genomic code", namely the code that determines how the precise temporal and spatial expression of each gene in the genome is achieved. In this regard, the elucidation of transcription regulatory networks that describe combined transcriptional circuits for an organism of interest has become valuable to our understanding of gene expression at a systems level. Such networks describe physical and regulatory interactions between transcription factors (TFs) and the target genes they regulate under different developmental, physiological, or pathological conditions. The mapping of high-quality transcription regulatory networks depends not only on the accuracy of the experimental or computational method chosen, but also relies on the quality of TF predictions. Moreover, the total repertoire of TFs is not only determined by the protein-coding capacity of the genome, but also by different protein properties, including dimerization, co-factor interactions and post-translational modifications. Here, we discuss the factors that influence TF functionality and, hence, the functionality of the networks in which they operate.

Mesh:

Substances:

Year:  2008        PMID: 18354784      PMCID: PMC2673723          DOI: 10.1039/b715909a

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  50 in total

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Journal:  Annu Rev Biophys Biomol Struct       Date:  1999

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Journal:  Nat Genet       Date:  2002-04-22       Impact factor: 38.330

Review 5.  Coregulator function: a key to understanding tissue specificity of selective receptor modulators.

Authors:  Carolyn L Smith; Bert W O'Malley
Journal:  Endocr Rev       Date:  2004-02       Impact factor: 19.871

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Journal:  Science       Date:  2003-12-19       Impact factor: 47.728

7.  Comprehensive identification of human bZIP interactions with coiled-coil arrays.

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8.  Ligand-independent recruitment of SRC-1 to estrogen receptor beta through phosphorylation of activation function AF-1.

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Review 9.  Activation of the aryl hydrocarbon receptor by structurally diverse exogenous and endogenous chemicals.

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Journal:  Bioessays       Date:  2009-04       Impact factor: 4.345

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4.  Transcription factor networks in Drosophila melanogaster.

Authors:  David Y Rhee; Dong-Yeon Cho; Bo Zhai; Matthew Slattery; Lijia Ma; Julian Mintseris; Christina Y Wong; Kevin P White; Susan E Celniker; Teresa M Przytycka; Steven P Gygi; Robert A Obar; Spyros Artavanis-Tsakonas
Journal:  Cell Rep       Date:  2014-09-18       Impact factor: 9.423

5.  Using a structural and logics systems approach to infer bHLH-DNA binding specificity determinants.

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Journal:  Nucleic Acids Res       Date:  2011-02-18       Impact factor: 16.971

6.  Tissue-specific regulation of mouse microRNA genes in endoderm-derived tissues.

Authors:  Yan Gao; Jonathan Schug; Lindsay B McKenna; John Le Lay; Klaus H Kaestner; Linda E Greenbaum
Journal:  Nucleic Acids Res       Date:  2010-09-14       Impact factor: 16.971

7.  TGFB1-Mediated Gliosis in Multiple Sclerosis Spinal Cords Is Favored by the Regionalized Expression of HOXA5 and the Age-Dependent Decline in Androgen Receptor Ligands.

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Journal:  Int J Mol Sci       Date:  2019-11-26       Impact factor: 5.923

8.  PITX1 Is a Regulator of TERT Expression in Prostate Cancer with Prognostic Power.

Authors:  Alexandra M Poos; Cornelia Schroeder; Neeraja Jaishankar; Daniela Röll; Marcus Oswald; Jan Meiners; Delia M Braun; Caroline Knotz; Lukas Frank; Manuel Gunkel; Roman Spilger; Thomas Wollmann; Adam Polonski; Georgia Makrypidi-Fraune; Christoph Fraune; Markus Graefen; Inn Chung; Alexander Stenzel; Holger Erfle; Karl Rohr; Aria Baniahmad; Guido Sauter; Karsten Rippe; Ronald Simon; Rainer Koenig
Journal:  Cancers (Basel)       Date:  2022-03-01       Impact factor: 6.639

9.  Integrated modeling and experimental approach for determining transcription factor profiles from fluorescent reporter data.

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  9 in total

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