motif finder
Recently Published Documents


TOTAL DOCUMENTS

19
(FIVE YEARS 0)

H-INDEX

7
(FIVE YEARS 0)

2019 ◽  
Vol 35 (22) ◽  
pp. 4632-4639 ◽  
Author(s):  
Yang Li ◽  
Pengyu Ni ◽  
Shaoqiang Zhang ◽  
Guojun Li ◽  
Zhengchang Su

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.


2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Jader M. Caldonazzo Garbelini ◽  
André Y. Kashiwabara ◽  
Danilo S. Sanches

PLoS ONE ◽  
2014 ◽  
Vol 9 (3) ◽  
pp. e90735 ◽  
Author(s):  
John E. Reid ◽  
Lorenz Wernisch

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

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

2012 ◽  
Vol 28 (16) ◽  
pp. 2213-2213 ◽  
Author(s):  
T. Wang ◽  
A. N. Kettenbach ◽  
S. A. Gerber ◽  
C. Bailey-Kellogg
Keyword(s):  

2012 ◽  
Vol 28 (12) ◽  
pp. 1562-1570 ◽  
Author(s):  
Tuobin Wang ◽  
Arminja N. Kettenbach ◽  
Scott A. Gerber ◽  
Chris Bailey-Kellogg
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document