Literature DB >> 18202457

Computational methods to dissect cis-regulatory transcriptional networks.

Vibha Rani1.   

Abstract

The formation of diverse cell types from an invariant set of genes is governed by biochemical and molecular processes that regulate gene activity. A complete understanding of the regulatory mechanisms of gene expression is the major function of genomics. Computational genomics is a rapidly emerging area for deciphering the regulation of metazoan genes as well as interpreting the results of high-throughput screening. The integration of computer science with biology has expedited molecular modelling and processing of large-scale data inputs such as microarrays, analysis of genomes, transcriptomes and proteomes. Many bioinformaticians have developed various algorithms for predicting transcriptional regulatory mechanisms from the sequence, gene expression and interaction data. This review contains compiled information of various computational methods adopted to dissect gene expression pathways.

Mesh:

Year:  2007        PMID: 18202457     DOI: 10.1007/s12038-007-0142-9

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  53 in total

1.  Regulatory element detection using correlation with expression.

Authors:  H J Bussemaker; H Li; E D Siggia
Journal:  Nat Genet       Date:  2001-02       Impact factor: 38.330

2.  Consensus promoter identification in the human genome utilizing expressed gene markers and gene modeling.

Authors:  Rongxiang Liu; David J States
Journal:  Genome Res       Date:  2002-03       Impact factor: 9.043

3.  Comparative promoter analysis and its application in analysis of PTH-regulated gene expression.

Authors:  Ping Qiu; Ling Qin; Richard P Sorrentino; Jonathan R Greene; Luquan Wang; Nicola C Partridge
Journal:  J Mol Biol       Date:  2003-03-07       Impact factor: 5.469

4.  Computational identification of transcription factor binding sites via a transcription-factor-centric clustering (TFCC) algorithm.

Authors:  Zhou Zhu; Yitzhak Pilpel; George M Church
Journal:  J Mol Biol       Date:  2002-04-19       Impact factor: 5.469

5.  Functional cloning, sorting, and expression profiling of nucleic acid-binding proteins.

Authors:  Y Ramanathan; Haibo Zhang; Virginie Aris; Patricia Soteropoulos; Stuart A Aaronson; Peter P Tolias
Journal:  Genome Res       Date:  2002-08       Impact factor: 9.043

Review 6.  Locating mammalian transcription factor binding sites: a survey of computational and experimental techniques.

Authors:  Laura Elnitski; Victor X Jin; Peggy J Farnham; Steven J M Jones
Journal:  Genome Res       Date:  2006-10-19       Impact factor: 9.043

7.  Large-scale human promoter mapping using CpG islands.

Authors:  I P Ioshikhes; M Q Zhang
Journal:  Nat Genet       Date:  2000-09       Impact factor: 38.330

8.  Human-mouse genome comparisons to locate regulatory sites.

Authors:  W W Wasserman; M Palumbo; W Thompson; J W Fickett; C E Lawrence
Journal:  Nat Genet       Date:  2000-10       Impact factor: 38.330

9.  Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies.

Authors:  J van Helden; B André; J Collado-Vides
Journal:  J Mol Biol       Date:  1998-09-04       Impact factor: 5.469

10.  TRED: a transcriptional regulatory element database, new entries and other development.

Authors:  C Jiang; Z Xuan; F Zhao; M Q Zhang
Journal:  Nucleic Acids Res       Date:  2007-01       Impact factor: 16.971

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  4 in total

1.  Prediction and validation of cis-regulatory elements in 5' upstream regulatory regions of lectin receptor-like kinase gene family in rice.

Authors:  Nishat Passricha; Shabnam Saifi; Mohammad W Ansari; Narendra Tuteja
Journal:  Protoplasma       Date:  2016-05-18       Impact factor: 3.356

2.  A study on the regulatory network with promoter analysis for Arabidopsis DREB-genes.

Authors:  Sima Sazegari; Ali Niazi; Farajolah Shahriary Ahmadi
Journal:  Bioinformation       Date:  2015-02-28

3.  Evolution and expression analyses of the MADS-box gene family in Brassica napus.

Authors:  Yunwen Wu; Yunzhuo Ke; Jing Wen; Pengcheng Guo; Feng Ran; Mangmang Wang; Mingming Liu; Pengfeng Li; Jiana Li; Hai Du
Journal:  PLoS One       Date:  2018-07-19       Impact factor: 3.240

4.  Genome-wide characterization, expression analyses, and functional prediction of the NPF family in Brassica napus.

Authors:  Jing Wen; Peng-Feng Li; Feng Ran; Peng-Cheng Guo; Jia-Tian Zhu; Jin Yang; Lan-Lan Zhang; Ping Chen; Jia-Na Li; Hai Du
Journal:  BMC Genomics       Date:  2020-12-07       Impact factor: 3.969

  4 in total

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