Seeder: discriminative seeding DNA motif discovery.

Bioinformatics
François FauteuxMartina V Strömvik

Abstract

The computational identification of transcription factor binding sites is a major challenge in bioinformatics and an important complement to experimental approaches. We describe a novel, exact discriminative seeding DNA motif discovery algorithm designed for fast and reliable prediction of cis-regulatory elements in eukaryotic promoters. The algorithm is tested on biological benchmark data and shown to perform equally or better than other motif discovery tools. The algorithm is applied to the analysis of plant tissue-specific promoter sequences and successfully identifies key regulatory elements.

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Citations

May 30, 2009·Bioinformatics·Tobias Marschall, Sven Rahmann
Jul 15, 2011·Bioinformatics·Peter HugginsZiv Bar-Joseph
Jun 18, 2011·BMC Bioinformatics·Shaoqiang ZhangZhengchang Su
Oct 22, 2009·BMC Plant Biology·François Fauteux, Martina V Strömvik
Nov 13, 2012·PloS One·David SimchaDonald Geman
May 30, 2014·PloS One·Aqil M Azmi, Abdulrakeeb Al-Ssulami
Jul 10, 2009·Yi chuan = Hereditas·Lin HouMing-Hua Deng
Dec 27, 2013·Bioinformatics·Ronak Y Patel, Gary D Stormo
Oct 25, 2014·BMC Genomics·Federico AgostiniGian Gaetano Tartaglia
Feb 16, 2010·Journal of Theoretical Biology·Jia-wei Luo, Ting Wang
Jul 13, 2016·The Plant Journal : for Cell and Molecular Biology·Ryan S AustinNicholas J Provart
Jun 3, 2017·Journal of Bioinformatics and Computational Biology·Abdulrakeeb M Al-SsulamiHassan Mathkour
Jun 14, 2017·Scientific Reports·Hongbo ZhangDe-Shuang Huang
May 8, 2018·Nucleic Acids Research·Meng NiuZhengchang Su
Aug 6, 2021·Briefings in Bioinformatics·Stefano CastellanaTommaso Mazza

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Software Mentioned

STAMP
Weeder
custom Perl script
Motif Sampler
MEME
INCLUSive CreateBackgroundModel
genomebg
Seeder
BioProspector

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