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Caleb Choo

dblp:122/2427 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genomic variant analysis
0.412019
MAVIS: merging, annotation, validation, and illustration of structural variants · Bioinform. 2019
Bioinformatics and computational biology › genomics › structural variation
structural variant detection
0.412019
MAVIS: merging, annotation, validation, and illustration of structural variants · Bioinform. 2019
Bioinformatics and computational biology
comparative genomics
0.112012
FeatureStack: Perl module for comparative visualization of gene features · Bioinform. 2012
Bioinformatics and computational biology › comparative genomics
gene family analysis
0.012012
FeatureStack: Perl module for comparative visualization of gene features · Bioinform. 2012

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

visualization · 0.1
YearPublicationVenuePosition
2019 MAVIS: merging, annotation, validation, and illustration of structural variants
abstract
Summary: Reliably identifying genomic rearrangements and interpreting their impact is a key step in understanding their role in human cancers and inherited genetic diseases. Many short read algorithmic approaches exist but all have appreciable false negative rates. A common approach is to evaluate the union of multiple tools increasing sensitivity, followed by filtering to retain specificity. Here we describe an application framework for the rapid generation of structural variant consensus, unique in its ability to visualize the genetic impact and context as well as process both genome and transcriptome data. Availability and implementation: http://mavis.bcgsc.ca. Supplementary information: Supplementary data are available at Bioinformatics online.
Caralyn Reisle, Karen L. Mungall, Caleb Choo, Daniel Paulino, Dustin W. Bleile, Amir Muhammadzadeh, Andrew J. Mungall, Richard A. Moore, Inna Shlafman, Robin Coope, Stephen Pleasance, Yussanne Ma, Steven J. M. Jones
Bioinform.3
2012 FeatureStack: Perl module for comparative visualization of gene features
abstract
SUMMARY: FeatureStack is a Perl module for the automatic generation of multi-gene images. FeatureStack takes BioPerl-compliant gene or transcript features as input and renders them side by side using a user-defined BioPerl glyph. Output images can be generated in SVG or PNG format. FeatureStack comes with a new BioPerl glyph, decorated_gene, which can highlight protein features on top of gene models. Used in combination, FeatureStack and decorated_gene enable rapid and automated generation of annotation-rich images of stacked gene models that greatly facilitate evolutionary studies of related gene structures and gene families. AVAILABILITY AND IMPLEMENTATION: Bio-Draw-FeatureStack and Bio-Graphics-glyph-decorated_gene are freely available at the Comprehensive Perl Archive Network (CPAN) and GitHub. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Christian Frech, Caleb Choo, Nansheng Chen
Bioinform.2