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Monkol Lek

dblp:00/5567 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · unresolved

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 · 88% Medical and health informatics · 12%

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
mitochondrial genomics
0.612022
MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022
Bioinformatics and computational biology › RNA biology › RNA analysis › RNA bioinformatics
RNA structure analysis
0.612022
MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022
Medical and health informatics
clinical genomics
0.212022
MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022
Bioinformatics and computational biology › clinical bioinformatics
variant interpretation
0.212022
MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA · Bioinform. 2022

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

RNA secondary structure visualization · 0.6
YearPublicationVenuePosition
2022 MitoVisualize: a resource for analysis of variants in human mitochondrial RNAs and DNA
abstract
SUMMARY: We present MitoVisualize, a new tool for analysis of the human mitochondrial DNA (mtDNA). MitoVisualize enables visualization of: (i) the position and effect of variants in mitochondrial transfer RNA and ribosomal RNA secondary structures alongside curated variant annotations, (ii) data across RNA structures, such as to show all positions with disease-associated variants or with post-transcriptional modifications and (iii) the position of a base, gene or region in the circular mtDNA map, such as to show the location of a large deletion. All visualizations can be easily downloaded as figures for reuse. MitoVisualize can be useful for anyone interested in exploring mtDNA variation, though is designed to facilitate mtDNA variant interpretation in particular. AVAILABILITY AND IMPLEMENTATION: MitoVisualize can be accessed via https://www.mitovisualize.org/. The source code is available at https://github.com/leklab/mito_visualize/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Nicole J. Lake, Lily Zhou, Jenny Xu, Monkol Lek
Bioinform.4