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Petri Martinmäki

dblp:94/7591 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2009
—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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis › sequence motif analysis
position weight matrix matching
0.112009
MOODS: fast search for position weight matrix matches in DNA sequences · Bioinform. 2009
Bioinformatics and computational biology › sequence analysis
sequence motif analysis
0.112009
MOODS: fast search for position weight matrix matches in DNA sequences · Bioinform. 2009
Bioinformatics and computational biology › sequence analysis
DNA sequence analysis
0.012009
MOODS: fast search for position weight matrix matches in DNA sequences · Bioinform. 2009

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

online matching algorithms · 0.1
YearPublicationVenuePosition
2009 MOODS: fast search for position weight matrix matches in DNA sequences
abstract
UNLABELLED: MOODS (MOtif Occurrence Detection Suite) is a software package for matching position weight matrices against DNA sequences. MOODS implements state-of-the-art online matching algorithms, achieving considerably faster scanning speed than with a simple brute-force search. MOODS is written in C++, with bindings for the popular BioPerl and Biopython toolkits. It can easily be adapted for different purposes and integrated into existing workflows. It can also be used as a C++ library. AVAILABILITY: The package with documentation and examples of usage is available at http://www.cs.helsinki.fi/group/pssmfind. The source code is also available under the terms of a GNU General Public License (GPL).
Janne H. Korhonen, Petri Martinmäki, Cinzia Pizzi, Pasi Rastas, Esko Ukkonen
Bioinform.2