• Publications
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Exploration, normalization, and summaries of high density oligonucleotide array probe level data.
In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip system with the objective of improving upon currently used measures of geneExpand
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Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1.
The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM intoExpand
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A comparison of normalization methods for high density oligonucleotide array data based on variance and bias
MOTIVATION When running experiments that involve multiple high density oligonucleotide arrays, it is important to remove sources of variation between arrays of non-biological origin. Normalization isExpand
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Summaries of Affymetrix GeneChip probe level data.
High density oligonucleotide array technology is widely used in many areas of biomedical research for quantitative and highly parallel measurements of gene expression. Affymetrix GeneChip arrays areExpand
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Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.
There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescentExpand
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Integrated Genomic Analyses of Ovarian Carcinoma
A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients’ lives. The Cancer Genome Atlas project has analysedExpand
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GOstat: find statistically overrepresented Gene Ontologies within a group of genes.
SUMMARY Modern experimental techniques, as for example DNA microarrays, as a result usually produce a long list of genes, which are potentially interesting in the analyzed process. In order to gainExpand
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Normalization of RNA-seq data using factor analysis of control genes or samples
Normalization of RNA-sequencing (RNA-seq) data has proven essential to ensure accurate inference of expression levels. Here, we show that usual normalization approaches mostly account for sequencingExpand
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Comprehensive genomic characterization defines human glioblastoma genes and core pathways
Human cancer cells typically harbour multiple chromosomal aberrations, nucleotide substitutions and epigenetic modifications that drive malignant transformation. The Cancer Genome Atlas (TCGA) pilotExpand
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Biological sequence analysis
  • T. Speed
  • Mathematics, Biology
  • 24 April 2003
This talk will review a little over a decade's research on applying certain stochastic models to biological sequence analysis. The models themselves have a longer history, going back over 30 years,Expand
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