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Jan Sliski

dblp:198/8426 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
comparative genomics
0.312017
ORCAN - a web-based meta-server for real-time detection and functional annotation of orthologs · Bioinform. 2017
Bioinformatics and computational biology › genome annotation
functional annotation
0.312017
ORCAN - a web-based meta-server for real-time detection and functional annotation of orthologs · Bioinform. 2017
Bioinformatics and computational biology › comparative genomics › orthology analysis
ortholog identification
0.312017
ORCAN - a web-based meta-server for real-time detection and functional annotation of orthologs · Bioinform. 2017
Bioinformatics and computational biology
protein function prediction
0.312017
ORCAN - a web-based meta-server for real-time detection and functional annotation of orthologs · Bioinform. 2017

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

plurality-based rating · 0.3
YearPublicationVenuePosition
2017 ORCAN - a web-based meta-server for real-time detection and functional annotation of orthologs
abstract
Summary: ORCAN (ORtholog sCANner) is a web-based meta-server for one-click evolutionary and functional annotation of protein sequences. The server combines information from the most popular orthology-prediction resources, including four tools and four online databases. Functional annotation utilizes five additional comparisons between the query and identified homologs, including: sequence similarity, protein domain architectures, functional motifs, Gene Ontology term assignments and a list of associated articles. Furthermore, the server uses a plurality-based rating system to evaluate the orthology relationships and to rank the reference proteins by their evolutionary and functional relevance to the query. Using a dataset of ∼1 million true yeast orthologs as a sample reference set, we show that combining multiple orthology-prediction tools in ORCAN increases the sensitivity and precision by 1-2 percent points. Availability and Implementation: The service is available for free at http://www.combio.pl/orcan/ . Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Andrzej Zielezinski, Michal Dziubek, Jan Sliski, Wojciech M. Karlowski
Bioinform.3