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Panayot Garnev

dblp:61/8322 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › immunoinformatics
epitope prediction		 0.112010
EpiTOP - a proteochemometric tool for MHC class II binding prediction · Bioinform. 2010
Bioinformatics and computational biology
immunoinformatics		 0.112010
EpiTOP - a proteochemometric tool for MHC class II binding prediction · Bioinform. 2010
Bioinformatics and computational biology › immunoinformatics
MHC class II binding prediction		 0.112010
EpiTOP - a proteochemometric tool for MHC class II binding prediction · Bioinform. 2010
Bioinformatics and computational biology › molecular informatics › cheminformatics
proteochemometrics		 0.012010
EpiTOP - a proteochemometric tool for MHC class II binding prediction · Bioinform. 2010
Bioinformatics and computational biology › molecular informatics › cheminformatics
quantitative structure-activity relationship		 0.012010
EpiTOP - a proteochemometric tool for MHC class II binding prediction · Bioinform. 2010

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

quantitative matrix · 0.1proteochemometrics · 0.1
YearPublicationVenuePosition
2010 EpiTOP - a proteochemometric tool for MHC class II binding prediction
abstract
MOTIVATION: T-cell epitope identification is a critical immunoinformatic problem within vaccine design. To be an epitope, a peptide must bind an MHC protein. RESULTS: Here, we present EpiTOP, the first server predicting MHC class II binding based on proteochemometrics, a QSAR approach for ligands binding to several related proteins. EpiTOP uses a quantitative matrix to predict binding to 12 HLA-DRB1 alleles. It identifies 89% of known epitopes within the top 20% of predicted binders, reducing laboratory labour, materials and time by 80%. EpiTOP is easy to use, gives comprehensive quantitative predictions and will be expanded and updated with new quantitative matrices over time. AVAILABILITY: EpiTOP is freely accessible at http://www.pharmfac.net/EpiTOP.
Ivan Dimitrov, Panayot Garnev, Darren R. Flower, Irini A. Doytchinova
 Bioinform.2