MOTIVATION Array comparative genomic hybridization (arrayCGH) is widely used to measure DNA copy numbers in cancer research. ArrayCGH data report log-ratio intensities of thousands of probes sampled along the chromosomes. Typically, the choices of the locations and the lengths of the probes vary in different experiments. This discrepancy in choosing probes poses a challenge in integrated classi...

Motivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profi...

Fluorescent cis-platinum compounds that react with the N7 atom of guanine are useful for labeling nucleic acids influorescence hybridization applications. Here we report that cyanin (CyN) cis-platinum labeling of DNA samples for array comparative genomic hybridizations (arrayCGH) can be achieved reproducibly and reliably. We demonstrate that degrees of labeling of approximately 1% of all nucleo...

Analysis of ArrayCGH Data for the Estimation of Genetic Tumor Progression Laura Toloşi Master of Science Department of Computer Science Saarland University 2006 In cancer research, prediction of time to death or relapse is important for a meaningful tumor classification and selecting appropriate therapies. The accumulation of genetic alterations during tumor progression can be used for the asse...

Lung squamous cell cancer (SCC) is typically found in smokers and has a very low incidence in non-smokers, indicating differences in the tumor biology of lung SCC in smokers and non-smokers. However, the specific mutations that drive tumor growth in non-smokers have not been identified. To identify mutations in lung SCC of non-smokers, we performed a genetic analysis using arrays comparative ge...

MOTIVATION Incorporating biological prior knowledge into predictive models is a challenging data integration problem in analyzing high-dimensional genomic data. We introduce a hypergraph-based semi-supervised learning algorithm called HyperPrior to classify gene expression and array-based comparative genomic hybridization (arrayCGH) data using biological knowledge as constraints on graph-based ...

MOTIVATION Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profil...

MicroRNAs (miRNAs) are a family of small, non-coding RNA species functioning as negative regulators of multiple target genes including tumour suppressor genes and oncogenes. Many miRNA gene loci are located within cancer-associated genomic regions. To identify potential new amplified oncogenic and/or deleted tumour suppressing miRNAs in lung cancer, we inferred miRNA gene dosage from high dimen...