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Moli Huang

dblp:69/9514 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
0000-0001-5543-9334ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
cancer epigenomics
0.412020
dbInDel: a database of enhancer-associated insertion and deletion variants by analysis of H3K27ac ChIP-Seq · Bioinform. 2020
Bioinformatics and computational biology › gene regulation
regulatory genomics
0.112020
dbInDel: a database of enhancer-associated insertion and deletion variants by analysis of H3K27ac ChIP-Seq · Bioinform. 2020

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

motif identification · 0.4ChIP-seq analysis · 0.4
YearPublicationVenuePosition
2020 dbInDel: a database of enhancer-associated insertion and deletion variants by analysis of H3K27ac ChIP-Seq
abstract
SUMMARY: Cancer hallmarks rely on its specific transcriptional programs, which are dysregulated by multiple mechanisms, including genomic aberrations in the DNA regulatory regions. Genome-wide association studies have shown many variants are found within putative enhancer elements. To provide insights into the regulatory role of enhancer-associated non-coding variants in cancer epigenome, and to facilitate the identification of functional non-coding mutations, we present dbInDel, a database where we have comprehensively analyzed enhancer-associated insertion and deletion variants for both human and murine samples using ChIP-Seq data. Moreover, we provide the identification and visualization of upstream TF binding motifs in InDel-containing enhancers. Downstream target genes are also predicted and analyzed in the context of cancer biology. The dbInDel database promotes the investigation of functional contributions of non-coding variants in cancer epigenome. AVAILABILITY AND IMPLEMENTATION: The database, dbInDel, can be accessed from http://enhancer-indel.cam-su.org/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Moli Huang, Manqiu Yang, Henry Yang, Wenzhuo Zhuang, H. Phillip Koeffler, De-Chen Lin, Xi Chen 0039
Bioinform.1