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Matthieu Moisse

dblp:135/5831 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
0000-0001-8880-9311ORCID · reported

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 › genomics › genome visualization
structural variant visualization
0.212013
Pipit: visualizing functional impacts of structural variations · Bioinform. 2013
Bioinformatics and computational biology › population genetics
genetic variation analysis
0.012013
Pipit: visualizing functional impacts of structural variations · Bioinform. 2013

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

interactive visualization · 0.2
YearPublicationVenuePosition
2013 Pipit: visualizing functional impacts of structural variations
abstract
Abstract Summary: Pipit is a gene-centric interactive visualization tool designed to study structural genomic variations. Through focusing on individual genes as the functional unit, researchers are able to study and generate hypotheses on the biological impact of different structural variations, for instance, the deletion of dosage-sensitive genes or the formation of fusion genes. Pipit is a cross-platform Java application that visualizes structural variation data from Genome Variation Format files. Availability: Executables, source code, sample data, documentation and screencast are available at https://bitbucket.org/biovizleuven/pipit. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Ryo Sakai, Matthieu Moisse, Joke Reumers, Jan Aerts
Bioinform.2