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Wojciech Makalowski

dblp:34/5258 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2009
0000-0003-2303-9541ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
genome annotation
0.011990
Searching for tRNA genes in DNA sequences--an IBM microcomputer program · Comput. Appl. Biosci. 1990
Bioinformatics and computational biology › genome annotation › gene prediction
tRNA gene search
0.011990
Searching for tRNA genes in DNA sequences--an IBM microcomputer program · Comput. Appl. Biosci. 1990
Bioinformatics and computational biology › biological database
sequence database access
0.011990
Searching for tRNA genes in DNA sequences--an IBM microcomputer program · Comput. Appl. Biosci. 1990

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

support vector machine · 0.1oligomer frequency · 0.1sequence pattern matching · 0.0
YearPublicationVenuePosition
2009 TEclass - a tool for automated classification of unknown eukaryotic transposable elements
abstract
MOTIVATION: The large number of sequenced genomes required the development of software that reconstructs the consensus sequences of transposons and other repetitive elements. However, the available tools usually focus on the accurate identification of raw repeats and provide no information about the taxonomic position of the reconstructed consensi. TEclass is a tool to classify unknown transposable elements into their four main functional categories, which reflect their mode of transposition: DNA transposons, long terminal repeats (LTRs), long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs). TEclass uses machine learning support vector machine (SVM) for classification based on oligomer frequencies. It achieves 90-97% accuracy in the classification of novel DNA and LTR repeats, and 75% for LINEs and SINEs. AVAILABILITY: http://www.compgen.uni-muenster.de/teclass, stand alone program upon request.
György Abrusán, Norbert Grundmann, Luc DeMester, Wojciech Makalowski
Bioinform.4
1990 Searching for tRNA genes in DNA sequences--an IBM microcomputer program
abstract
A user-friendly program that enables fast and exhaustive searching for tRNA genes is presented. The program can run on IBM personal microcomputers and comprises modules for sequence editing and GenBank database access.
P. Wozniak, Wojciech Makalowski
Comput. Appl. Biosci.2