Literature DB >> 12666149

Characterization of transcription factors by mass spectrometry and the role of SELDI-MS.

Cameron E Forde1, Sandra L McCutchen-Maloney.   

Abstract

Over the last decade, much progress has been made in the field of biological mass spectrometry, with numerous advances in technology, resolution, and affinity capture. The field of genomics has also been transformed by the sequencing and characterization of entire genomes. Some of the next challenges lie in understanding the relationship between the genome and the proteome, the protein complement of the genome, and in characterizing the regulatory processes involved in progressing from gene to functional protein. In this new age of proteomics, development of mass spectrometry methods to characterize transcription factors promises to add greatly to our understanding of regulatory networks that govern expression. However, at this time, regulatory networks of transcription factors are mostly uncharted territory. In this review, we summarize the latest advances in characterization of transcription factors by mass spectrometry including affinity capture, identification of complexes of DNA-binding proteins, structural characterization, determination of protein-DNA and protein-protein interactions, assessment of modification sites and metal binding, studies of functional activity, and the latest chip technologies that use SELDI-MS that allow the rapid capture and identification of transcription factors. Copyright 2003 Wiley Periodicals, Inc.

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Year:  2002        PMID: 12666149     DOI: 10.1002/mas.10040

Source DB:  PubMed          Journal:  Mass Spectrom Rev        ISSN: 0277-7037            Impact factor:   10.946


  4 in total

Review 1.  Charting gene regulatory networks: strategies, challenges and perspectives.

Authors:  Gong-Hong Wei; De-Pei Liu; Chih-Chuan Liang
Journal:  Biochem J       Date:  2004-07-01       Impact factor: 3.857

2.  A role for the MS analysis of nucleic acids in the post-genomics age.

Authors:  Daniele Fabris
Journal:  J Am Soc Mass Spectrom       Date:  2009-09-17       Impact factor: 3.109

3.  Linear fuzzy gene network models obtained from microarray data by exhaustive search.

Authors:  Bahrad A Sokhansanj; J Patrick Fitch; Judy N Quong; Andrew A Quong
Journal:  BMC Bioinformatics       Date:  2004-08-10       Impact factor: 3.169

4.  Modeling Modulation of the Tick Regulome in Response to Anaplasma phagocytophilum for the Identification of New Control Targets.

Authors:  Sara Artigas-Jerónimo; Agustín Estrada-Peña; Alejandro Cabezas-Cruz; Pilar Alberdi; Margarita Villar; José de la Fuente
Journal:  Front Physiol       Date:  2019-04-18       Impact factor: 4.566

  4 in total

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