Literature DB >> 15961476

Predicting the in vivo signature of human gene regulatory sequences.

William Stafford Noble1, Scott Kuehn, Robert Thurman, Man Yu, John Stamatoyannopoulos.   

Abstract

MOTIVATION: In the living cell nucleus, genomic DNA is packaged into chromatin. DNA sequences that regulate transcription and other chromosomal processes are associated with local disruptions, or 'openings', in chromatin structure caused by the cooperative action of regulatory proteins. Such perturbations are extremely specific for cis-regulatory elements and occur over short stretches of DNA (typically approximately 250 bp). They can be detected experimentally as DNaseI hypersensitive sites (HSs) in vivo, though the process is extremely laborious and costly. The ability to discriminate DNaseI HSs computationally would have a major impact on the annotation and utilization of the human genome.
RESULTS: We found that a supervised pattern recognition algorithm, trained using a set of 280 DNaseI HS and 737 non-HS control sequences from erythroid cells, was capable of de novo prediction of HSs across the human genome with surprisingly high accuracy determined by prospective in vivo validation. Systematic application of this computational approach will greatly facilitate the discovery and analysis of functional non-coding elements in the human and other complex genomes. AVAILABILITY: Supplementary data is available at noble.gs.washington.edu/proj/hs

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Year:  2005        PMID: 15961476     DOI: 10.1093/bioinformatics/bti1047

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


  25 in total

1.  Genome-wide computational prediction of transcriptional regulatory modules reveals new insights into human gene expression.

Authors:  Mathieu Blanchette; Alain R Bataille; Xiaoyu Chen; Christian Poitras; Josée Laganière; Céline Lefèbvre; Geneviève Deblois; Vincent Giguère; Vincent Ferretti; Dominique Bergeron; Benoit Coulombe; François Robert
Journal:  Genome Res       Date:  2006-04-10       Impact factor: 9.043

Review 2.  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

3.  ESPERR: learning strong and weak signals in genomic sequence alignments to identify functional elements.

Authors:  James Taylor; Svitlana Tyekucheva; David C King; Ross C Hardison; Webb Miller; Francesca Chiaromonte
Journal:  Genome Res       Date:  2006-10-19       Impact factor: 9.043

Review 4.  Identifying regulatory elements in eukaryotic genomes.

Authors:  Leelavati Narlikar; Ivan Ovcharenko
Journal:  Brief Funct Genomic Proteomic       Date:  2009-06-04

5.  Detection of DNA structural motifs in functional genomic elements.

Authors:  Jason A Greenbaum; Stephen C J Parker; Thomas D Tullius
Journal:  Genome Res       Date:  2007-06       Impact factor: 9.043

6.  A protein activity assay to measure global transcription factor activity reveals determinants of chromatin accessibility.

Authors:  Bei Wei; Arttu Jolma; Biswajyoti Sahu; Lukas M Orre; Fan Zhong; Fangjie Zhu; Teemu Kivioja; Inderpreet Sur; Janne Lehtiö; Minna Taipale; Jussi Taipale
Journal:  Nat Biotechnol       Date:  2018-05-21       Impact factor: 54.908

7.  pDHS-ELM: computational predictor for plant DNase I hypersensitive sites based on extreme learning machines.

Authors:  Shanxin Zhang; Minjun Chang; Zhiping Zhou; Xiaofeng Dai; Zhenghong Xu
Journal:  Mol Genet Genomics       Date:  2018-03-29       Impact factor: 3.291

8.  2lpiRNApred: a two-layered integrated algorithm for identifying piRNAs and their functions based on LFE-GM feature selection.

Authors:  Yun Zuo; Quan Zou; Jianyuan Lin; Min Jiang; Xiangrong Liu
Journal:  RNA Biol       Date:  2020-03-05       Impact factor: 4.652

9.  iLearnPlus: a comprehensive and automated machine-learning platform for nucleic acid and protein sequence analysis, prediction and visualization.

Authors:  Zhen Chen; Pei Zhao; Chen Li; Fuyi Li; Dongxu Xiang; Yong-Zi Chen; Tatsuya Akutsu; Roger J Daly; Geoffrey I Webb; Quanzhi Zhao; Lukasz Kurgan; Jiangning Song
Journal:  Nucleic Acids Res       Date:  2021-06-04       Impact factor: 16.971

10.  Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences.

Authors:  Bin Liu; Fule Liu; Xiaolong Wang; Junjie Chen; Longyun Fang; Kuo-Chen Chou
Journal:  Nucleic Acids Res       Date:  2015-05-09       Impact factor: 16.971

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