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Björn Menten

dblp:66/1187 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2009
0000-0001-8182-659XORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

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 › gene expression analysis › microarray data analysis
array comparative genomic hybridization
0.112009
Smoothing waves in array CGH tumor profiles · Bioinform. 2009
Bioinformatics and computational biology › genomics
breakpoint detection
0.112009
Smoothing waves in array CGH tumor profiles · Bioinform. 2009
Bioinformatics and computational biology › cancer genomics › chromosomal aberration detection
copy number aberration detection
0.112009
Smoothing waves in array CGH tumor profiles · Bioinform. 2009

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

smoothing · 0.1regression · 0.1
YearPublicationVenuePosition
2009 Smoothing waves in array CGH tumor profiles
abstract
MOTIVATION: Many high-resolution array comparative genomic hybridization tumor profiles contain a wave bias, which makes accurate detection of breakpoints in such profiles more difficult. RESULTS: An efficient and highly effective algorithm that largely removes the wave bias from tumor profiles by regressing the tumor profile data on data of profiles from the clinical genetics practice. Results are illustrated on two independent datasets. The algorithm is shown to be robust against the presence of true copy number aberrations. Moreover, the smoothed profiles are able to recapitulate the aberration location and signal for simulated tumor profiles. AVAILABILITY: Easy-to-use R scripts, user instructions and data are available from http://www.few.vu.nl/~mavdwiel/nowaves.html. SUPPLEMENTARY INFORMATION: Supplementary information are available at Bioinformatics online.
Mark A. van de Wiel, Rebecca Brosens, Paul H. C. Eilers, Candy Kumps, Gerrit Meijer, Björn Menten, Erik Sistermans, Frank Speleman, Marieke E. Timmerman, Bauke Ylstra
Bioinform.6
2005 arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays
abstract
BACKGROUND: The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. RESULTS: We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. CONCLUSION: ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.
Björn Menten, Filip Pattyn, Katleen De Preter, Piet Robbrecht, Evi Michels, Karen Buysse, Geert Mortier, Anne De Paepe, Steven Van Vooren, Joris Robert Vermeesch, Yves Moreau, Bart De Moor, Stefan Vermeulen, Frank Speleman, Jo Vandesompele
BMC Bioinform.1