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Aibin He

dblp:56/9181 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0002-3489-2305ORCID · reported

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis
0.112011
CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments · Bioinform. 2011
Bioinformatics and computational biology
genomics
0.112011
CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments · Bioinform. 2011
Bioinformatics and computational biology › sequence analysis › motif discovery
transcription factor binding motif discovery
0.112011
CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments · Bioinform. 2011

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

motif scanning · 0.1enrichment testing · 0.1de novo motif discovery · 0.1
YearPublicationVenuePosition
2011 CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments
abstract
UNLABELLED: CompleteMOTIFs (cMOTIFs) is an integrated web tool developed to facilitate systematic discovery of overrepresented transcription factor binding motifs from high-throughput chromatin immunoprecipitation experiments. Comprehensive annotations and Boolean logic operations on multiple peak locations enable users to focus on genomic regions of interest for de novo motif discovery using tools such as MEME, Weeder and ChIPMunk. The pipeline incorporates a scanning tool for known motifs from TRANSFAC and JASPAR databases, and performs an enrichment test using local or precalculated background models that significantly improve the motif scanning result. Furthermore, using the cMOTIFs pipeline, we demonstrated that multiple transcription factors could cooperatively bind to the upstream of important stem cell differentiation regulators. AVAILABILITY: http://cmotifs.tchlab.org.
Lakshmi Kuttippurathu, Michael Hsing, Yongchao Liu 0004, Bertil Schmidt, Douglas L. Maskell, Kyungjoon Lee, Aibin He, William T. Pu, Sek Won Kong
Bioinform.7