Shen-Ying Zhang

dblp:235/8478 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genomics
0.312018
PopViz: a webserver for visualizing minor allele frequencies and damage prediction scores of human genetic variations · Bioinform. 2018
Bioinformatics and computational biology › genome annotation
genomic variant annotation
0.312018
PopViz: a webserver for visualizing minor allele frequencies and damage prediction scores of human genetic variations · Bioinform. 2018
Bioinformatics and computational biology › genomics › genome visualization
variant visualization
0.312018
PopViz: a webserver for visualizing minor allele frequencies and damage prediction scores of human genetic variations · Bioinform. 2018

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

web server · 0.3
YearPublicationVenuePosition
2018 PopViz: a webserver for visualizing minor allele frequencies and damage prediction scores of human genetic variations
abstract
Summary: Next-generation sequencing (NGS) generates large amounts of genomic data and reveals about 20 000 genetic coding variants per individual studied. Several mutation damage prediction scores are available to prioritize variants, but there is currently no application to help investigators to determine the relevance of the candidate genes and variants quickly and visually from population genetics data and deleteriousness scores. Here, we present PopViz, a user-friendly, rapid, interactive, mobile-compatible webserver providing a gene-centric visualization of the variants of any human gene, with (i) population-specific minor allele frequencies from the gnomAD population genetic database; (ii) mutation damage prediction scores from CADD, EIGEN and LINSIGHT and (iii) amino-acid positions and protein domains. This application will be particularly useful in investigations of NGS data for new disease-causing genes and variants, by reinforcing or rejecting the plausibility of the candidate genes, and by selecting and prioritizing, the candidate variants for experimental testing. Availability and implementation: PopViz webserver is freely accessible from http://shiva.rockefeller.edu/PopViz/. Supplementary information: Supplementary data are available at Bioinformatics online.
Peng Zhang 0033, Benedetta Bigio, Franck Rapaport, Shen-Ying Zhang, Jean-Laurent Casanova, Laurent Abel, Bertrand Boisson, Yuval Itan
Bioinform.4