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Hon-Ming Lam

dblp:330/4720 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0002-6673-8740ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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
comparative genomics
0.612022
ShinySyn: a Shiny/R application for the interactive visualization and integration of macro- and micro-synteny data · Bioinform. 2022
Bioinformatics and computational biology › comparative genomics
synteny analysis
0.612022
ShinySyn: a Shiny/R application for the interactive visualization and integration of macro- and micro-synteny data · Bioinform. 2022
Bioinformatics and computational biology › comparative genomics › synteny analysis
synteny visualization
0.612022
ShinySyn: a Shiny/R application for the interactive visualization and integration of macro- and micro-synteny data · Bioinform. 2022

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

shiny/r · 0.6MCscan · 0.6
YearPublicationVenuePosition
2022 ShinySyn: a Shiny/R application for the interactive visualization and integration of macro- and micro-synteny data
abstract
MOTIVATION: Synteny analysis is a widely used framework in comparative genomics studies, which provides valuable information to reveal chromosome collinearity in both intra-species and inter-species. Most analysis pipelines, however, are command line-based, making it challenging for biologists to run the algorithms and visualize the results. Existing visualization tools either provide static plots or can only be run on web-based servers and lack efficient visualization methods for associating macro-synteny blocks with individual gene pairs in a micro-synteny region. RESULTS: We developed ShinySyn, a Shiny/R application built on the MCscan framework that provides an easy-to-use graphic interface for synteny analyses without requiring any programming skills, to reduce technical barriers. ShinySyn not only provides interactive visualization for macro-synteny, micro-synteny and genome-level dot views, but it also creates an intuitive representation with a dynamic zooming feature from macro-synteny to individual homologous genes. AVAILABILITY AND IMPLEMENTATION: The source code and installation instructions for ShinySyn can be accessed via https://github.com/obenno/ShinySyn. A pre-built docker image is also available at https://hub.docker.com/r/obenno/shinysyn. The application can be used locally or seamlessly integrated into any Shiny application server.
Zhixia Xiao, Hon-Ming Lam
Bioinform.2