Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Chuan Zhou 0009

dblp:52/564-9 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › motif discovery
regulatory motif discovery
0.212013
An integrated toolkit for accurate prediction and analysis of cis-regulatory motifs at a genome scale · Bioinform. 2013

Methods — techniques the papers use, named apart from their topics

p-value estimation · 0.2dynamic programming · 0.2
YearPublicationVenuePosition
2013 An integrated toolkit for accurate prediction and analysis of cis-regulatory motifs at a genome scale
abstract
MOTIVATION: We present an integrated toolkit, BoBro2.0, for prediction and analysis of cis-regulatory motifs. This toolkit can (i) reliably identify statistically significant cis-regulatory motifs at a genome scale; (ii) accurately scan for all motif instances of a query motif in specified genomic regions using a novel method for P-value estimation; (iii) provide highly reliable comparisons and clustering of identified motifs, which takes into consideration the weak signals from the flanking regions of the motifs; and (iv) analyze co-occurring motifs in the regulatory regions. RESULTS: We have carried out systematic comparisons between motif predictions using BoBro2.0 and the MEME package. The comparison results on Escherichia coli K12 genome and the human genome show that BoBro2.0 can identify the statistically significant motifs at a genome scale more efficiently, identify motif instances more accurately and get more reliable motif clusters than MEME. In addition, BoBro2.0 provides correlational analyses among the identified motifs to facilitate the inference of joint regulation relationships of transcription factors. AVAILABILITY: The source code of the program is freely available for noncommercial uses at http://code.google.com/p/bobro/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Qin Ma 0003, Bingqiang Liu, Chuan Zhou 0009, Yanbin Yin, Ying Xu 0001
Bioinform.3