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Lim Heo

dblp:96/10356 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
—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
protein structure prediction
0.312018
PREFMD: a web server for protein structure refinement via molecular dynamics simulations · Bioinform. 2018
Bioinformatics and computational biology › protein structure prediction
protein structure refinement
0.312018
PREFMD: a web server for protein structure refinement via molecular dynamics simulations · Bioinform. 2018
Bioinformatics and computational biology
structural bioinformatics
0.112018
PREFMD: a web server for protein structure refinement via molecular dynamics simulations · Bioinform. 2018

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

molecular dynamics simulation · 0.3
YearPublicationVenuePosition
2018 PREFMD: a web server for protein structure refinement via molecular dynamics simulations
abstract
Summary: Refinement of protein structure models is a long-standing problem in structural bioinformatics. Molecular dynamics-based methods have emerged as an avenue to achieve consistent refinement. The PREFMD web server implements an optimized protocol based on the method successfully tested in CASP11. Validation with recent CASP refinement targets shows consistent and more significant improvement in global structure accuracy over other state-of-the-art servers. Availability and implementation: PREFMD is freely available as a web server at http://feiglab.org/prefmd. Scripts for running PREFMD as a stand-alone package are available at https://github.com/feiglab/prefmd.git. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Lim Heo, Michael Feig
Bioinform.1