scholarly journals Comments on 'MMFPh: A Maximal Motif Finder for Phosphoproteomics Datasets'

2012 ◽  
Vol 28 (16) ◽  
pp. 2211-2212 ◽  
Author(s):  
Z. He ◽  
H. Gong
Keyword(s):  
Motif Finder

scholarly journals STEME: A Robust, Accurate Motif Finder for Large Data Sets

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e90735 ◽  
Author(s):  
John E. Reid ◽  
Lorenz Wernisch
Keyword(s):  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Motif Finder

scholarly journals ProSampler: an ultrafast and accurate motif finder in large ChIP-seq datasets for combinatory motif discovery

2019 ◽  
Vol 35 (22) ◽  
pp. 4632-4639 ◽  
Author(s):  
Yang Li ◽  
Pengyu Ni ◽  
Shaoqiang Zhang ◽  
Guojun Li ◽  
Zhengchang Su
Keyword(s):  
Transcription Factors ◽  
Gibbs Sampler ◽  
Binding Sites ◽  
Motif Discovery ◽  
Source Code ◽  
Motif Finding ◽  
Supplementary Information ◽  
Highly Efficient ◽  
Motif Finder ◽  
Motif Finding Algorithm

Abstract Motivation The availability of numerous ChIP-seq datasets for transcription factors (TF) has provided an unprecedented opportunity to identify all TF binding sites in genomes. However, the progress has been hindered by the lack of a highly efficient and accurate tool to find not only the target motifs, but also cooperative motifs in very big datasets. Results We herein present an ultrafast and accurate motif-finding algorithm, ProSampler, based on a novel numeration method and Gibbs sampler. ProSampler runs orders of magnitude faster than the fastest existing tools while often more accurately identifying motifs of both the target TFs and cooperators. Thus, ProSampler can greatly facilitate the efforts to identify the entire cis-regulatory code in genomes. Availability and implementation Source code and binaries are freely available for download at https://github.com/zhengchangsulab/prosampler. It was implemented in C++ and supported on Linux, macOS and MS Windows platforms. Supplementary information Supplementary materials are available at Bioinformatics online.

SMOTER, A Structured Motif Finder Based on an Exhaustive Tree-Based Algorithm

2014 ◽  
Vol 9 (1) ◽  
pp. 34-43 ◽  
Author(s):  
Siavash Sheikhizadeh ◽  
Samin Hosseini
Keyword(s):  
Motif Finder ◽  
Structured Motif

scholarly journals PhyloGibbs: A Gibbs Sampling Motif Finder that Incorporates Phylogeny

2005 ◽  
Vol preprint (2005) ◽  
pp. e67 ◽  
Author(s):  
Rahul Siddharthan ◽  
Eric D Siggia ◽  
Erik Jan van Nimwegen
Keyword(s):  
Gibbs Sampling ◽  
Motif Finder

scholarly journals Efficient α, β-motif finder for identification of phenotype-related functional modules

2011 ◽  
Vol 12 (1) ◽  
pp. 440 ◽  
Author(s):  
Matthew C Schmidt ◽  
Andrea M Rocha ◽  
Kanchana Padmanabhan ◽  
Zhengzhang Chen ◽  
Kathleen Scott ◽  
...  
Keyword(s):  
Functional Modules ◽  
Motif Finder

scholarly journals iTriplet, a rule-based nucleic acid sequence motif finder

2009 ◽  
Vol 4 (1) ◽  
pp. 14 ◽  
Author(s):  
Eric S Ho ◽  
Christopher D Jakubowski ◽  
Samuel I Gunderson
Keyword(s):  
Nucleic Acid ◽  
Nucleic Acid Sequence ◽  
Sequence Motif ◽  
Rule Based ◽  
Motif Finder

scholarly journals Sequence motif finder using memetic algorithm

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Jader M. Caldonazzo Garbelini ◽  
André Y. Kashiwabara ◽  
Danilo S. Sanches
Keyword(s):  
Memetic Algorithm ◽  
Sequence Motif ◽  
Motif Finder

scholarly journals PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny

2005 ◽  
Vol 1 (7) ◽  
pp. e67 ◽  
Author(s):  
Rahul Siddharthan ◽  
Eric D Siggia ◽  
Erik van Nimwegen
Keyword(s):  
Gibbs Sampling ◽  
Motif Finder
Sign in / Sign up

Export Citation Format

Share Document