Paper Info
Title
SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets.
Abstract
Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.
Year
DOI
Venue
2007
10.1186/1471-2105-8-422
BMC Bioinformatics
Keywords
Field
DocType
algorithms,array comparative genomic hybridization,microarrays,biological process,breast cancer,in situ hybridization,artificial intelligence,bioinformatics
Disease,Gene,Biology,DNA,DNA Mutational Analysis,Bioinformatics,Genetics,In situ hybridization,Comparative Genome Hybridization,DNA microarray,Cancer
Journal
Volume
Issue
ISSN
8
1
1471-2105
Citations 
PageRank 
References 
15
0.38
4
Authors
7
Name
Order
Citations
PageRank
Carmen Lai12039.03
Hugo M Horlings2150.38
Marc J van de Vijver3150.38
Eric H van Beers4150.38
Petra M Nederlof5150.38
Lodewyk F A Wessels633722.28
Marcel J. T. Reinders71556104.09