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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
It is demonstrated how the GSEA method yields insights into several cancer-related data sets, including leukemia and lung cancer, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer. Expand
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge. Expand
PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes
An analytical strategy is introduced, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes, which identifies a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expand
The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity
The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens. Expand
The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease
The first installment of a reference collection of gene-expression profiles from cultured human cells treated with bioactive small molecules is created, and it is demonstrated that this “Connectivity Map” resource can be used to find connections among small molecules sharing a mechanism of action, chemicals and physiological processes, and diseases and drugs. Expand
MicroRNA expression profiles classify human cancers
A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours. Expand
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Michael S. Lawrence*, Petar Stojanov*, Paz Polak*, Gregory V. Kryukov, Kristian Cibulskis, Andrey Sivachenko, Scott L. Carter, Chip Stewart, Craig H. Mermel, Steven A. Roberts, Adam Kiezun, Peter S.Expand
Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation.
The application of self-organizing maps, a type of mathematical cluster analysis that is particularly well suited for recognizing and classifying features in complex, multidimensional data, is described. Expand
Metagenes and molecular pattern discovery using matrix factorization
Nonnegative matrix factorization is described, an algorithm based on decomposition by parts that can reduce the dimension of expression data from thousands of genes to a handful of metagenes, and found less sensitive to a priori selection of genes or initial conditions and able to detect alternative or context-dependent patterns of gene expression in complex biological systems. Expand
The Mutational Landscape of Head and Neck Squamous Cell Carcinoma
The results indicate the ability of large-scale sequencing to reveal fundamental tumorigenic mechanisms and suggest the development of targeted therapies for head and neck cancer may be hindered by complex mutational profiles. Expand