Pablo Tamayo

Molecular signatures database (MSigDB) 3.0

Abstract Motivation: Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale geno...

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring

Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumo...

PGC-1α-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes

Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1

Interpreting patterns of gene expression with self-organizing maps: Methods and application to hematopoietic differentiation

Array technologies have made it straightforward to monitor simultaneously the expression pattern of thousands of genes. The challenge now is to interpret such massive data sets....

Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning

Multiclass cancer diagnosis using tumor gene expression signatures

The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances...

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here...

Chemosensitivity prediction by transcriptional profiling

In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on ge...

Systematic Evaluation of Molecular Networks for Discovery of Disease Genes

Gene networks are rapidly growing in size and number, raising the question of which networks are most appropriate for particular applications. Here, we evaluate 21 human genome-...

<i>GSEA-P</i>: a desktop application for Gene Set Enrichment Analysis

Abstract Gene Set Enrichment Analysis (GSEA) is a computational method that assesses whether an a priori defined set of genes shows statistically significant, concordant differe...