Secure Motif Finding Based on Candidate Pruning

2020 ◽  
Author(s):  
Kaijian Xia ◽  
Xiang Wu ◽  
Yaqing Mao ◽  
Huanhuan Wang
Keyword(s):  
Motif Finding

scholarly journals A cost-aggregating integer linear program for motif finding

2011 ◽  
Vol 9 (4) ◽  
pp. 326-334 ◽  
Author(s):  
Carl Kingsford ◽  
Elena Zaslavsky ◽  
Mona Singh
Keyword(s):  
Linear Program ◽  
Integer Linear Program ◽  
Motif Finding

ACoM: A classification method for elementary flux modes based on motif finding

Biosystems ◽  
2011 ◽  
Vol 103 (3) ◽  
pp. 410-419 ◽  
Author(s):  
S. Pérès ◽  
F. Vallée ◽  
M. Beurton-Aimar ◽  
J.P. Mazat
Keyword(s):  
Classification Method ◽  
Motif Finding ◽  
Elementary Flux Modes

Motif Finding

2016 ◽  
Vol 2017 (2) ◽  
pp. pdb.top093195 ◽  
Author(s):  
Jui-Hung Hung ◽  
Zhiping Weng
Keyword(s):  
Motif Finding

scholarly journals DNA Motif Finding Method Without Protection Can Leak User Privacy

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 152076-152087
Author(s):  
Xiang Wu ◽  
Huanhuan Wang ◽  
Minyu Shi ◽  
Aming Wang ◽  
Kaijian Xia
Keyword(s):  
Motif Finding ◽  
User Privacy ◽  
Dna Motif ◽  
Finding Method

scholarly journals MFEA: An evolutionary approach for motif finding in DNA sequences

2020 ◽  
Vol 21 ◽  
pp. 100466
Author(s):  
Faisal Bin Ashraf ◽  
Md Shafiur Raihan Shafi
Keyword(s):  
Dna Sequences ◽  
Motif Finding ◽  
Evolutionary Approach

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.

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