Share This Author
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
- A. Subramanian, P. Tamayo, J. Mesirov
- BiologyProceedings of the National Academy of Sciences…
- 30 September 2005
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.
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.
Integrative Genomics Viewer
The sheer volume and scope of data posed by this flood of data pose a significant challenge to the development of efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data.
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.
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.
Integrated genomic analysis identifies clinically relevant subtypes of glioblastoma characterized by abnormalities in PDGFRA, IDH1, EGFR, and NF1.
Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration
The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution.
Initial sequencing and analysis of the human genome.
The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Molecular signatures database (MSigDB) 3.0
- A. Liberzon, A. Subramanian, Reid Pinchback, H. Thorvaldsdóttir, P. Tamayo, J. Mesirov
- 1 June 2011
A new version of the database, MSigDB 3.0, is reported, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site.
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.