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I. Selimas

dblp:50/1873 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biomedical text mining		 0.112005
METIS: multiple extraction techniques for informative sentences · Bioinform. 2005
Bioinformatics and computational biology › protein analysis › protein bioinformatics
protein family annotation		 0.012005
METIS: multiple extraction techniques for informative sentences · Bioinform. 2005

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

support vector machine · 0.1rule-based sentence classification · 0.1
YearPublicationVenuePosition
2005 METIS: multiple extraction techniques for informative sentences
abstract
SUMMARY: METIS is a web-based integrated annotation tool. From single query sequences, the PRECIS component allows users to generate structured protein family reports from sets of related Swiss-Prot entries. These reports may then be augmented with pertinent sentences extracted from online biomedical literature via support vector machine and rule-based sentence classification systems. AVAILABILITY: http://umber.sbs.man.ac.uk/dbbrowser/metis/
Alex L. Mitchell, Anna Divoli, Jee-Hyub Kim, Melanie Hilario, I. Selimas, Terri K. Attwood
 Bioinform.5