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Chul Joo Kang

dblp:12/11133 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · unresolved

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › population genetics › population genetics simulation
coalescent simulation
0.112012
Exact coalescent simulation of new haplotype data from existing reference haplotypes · Bioinform. 2012
Bioinformatics and computational biology › population genetics › population genetics simulation
haplotype simulation
0.112012
Exact coalescent simulation of new haplotype data from existing reference haplotypes · Bioinform. 2012
Bioinformatics and computational biology
population genetics
0.112012
Exact coalescent simulation of new haplotype data from existing reference haplotypes · Bioinform. 2012

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

markov chain monte carlo · 0.1coalescent theory · 0.1
YearPublicationVenuePosition
2012 Exact coalescent simulation of new haplotype data from existing reference haplotypes
abstract
Abstract Motivation: We introduce a coalescent-based method (RECOAL) for the simulation of new haplotype data from a reference population of haplotypes. A coalescent genealogy for the reference haplotype data is sampled from the appropriate posterior probability distribution, then a coalescent genealogy is simulated which extends the sampled genealogy to include new haplotype data. The new haplotype data will, therefore, contain both some of the existing polymorphic sites and new polymorphisms added based on the structure of the simulated coalescent genealogy. This allows exact coalescent simulation of new haplotype data, compared with other methods which are more approximate in nature. Results: We demonstrate the performance of our method using a variety of data simulated under a coalescent model, before applying it to data from the 1000 Genomes project. Availability: The source code is freely available for download at ftp://popgen.usc.edu Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Chul Joo Kang, Paul Marjoram
Bioinform.1