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Núria Malats

dblp:20/8712 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0003-2538-3784ORCID · 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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › statistical genetics
gene-gene interaction
0.112010
mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits · Bioinform. 2010
Bioinformatics and computational biology › statistical genetics
genetic association study
0.112010
mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits · Bioinform. 2010
Bioinformatics and computational biology › statistical genetics
multifactor dimensionality reduction
0.112010
mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits · Bioinform. 2010
Bioinformatics and computational biology
case-control study
0.012010
mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits · Bioinform. 2010

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

regression modeling · 0.1dimension reduction · 0.1
YearPublicationVenuePosition
2010 mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits
abstract
SUMMARY: We describe mbmdr, an R package for implementing the model-based multifactor dimensionality reduction (MB-MDR) method. MB-MDR has been proposed by Calle et al. as a dimension reduction method for exploring gene-gene interactions in case-control association studies. It is an extension of the popular multifactor dimensionality reduction (MDR) method of Ritchie et al. allowing a more flexible definition of risk cells. In MB-MDR, risk categories are defined using a regression model which allows adjustment for covariates and main effects and, in addition to the classical low risk and high risk categories, MB-MDR considers a third category of indeterminate or not informative cells. An important improvement added to the current mbmdr algorithm with respect to the original MB-MDR formulation in Calle et al. and also to the classical MDR approach, is the extension of the methodology to different outcome types. While MB-MDR was initially proposed for binary traits in the context of case-control studies, the mbmdr package provides options to analyze both binary or quantitative traits for unrelated individuals. AVAILABILITY: http://cran.r-project.org/.
Malu Luz Calle, Víctor Urrea, Núria Malats, Kristel Van Steen
Bioinform.3