Jill P Mesirov
Biographic Data
| ID | 10713633 |
|---|---|
| NAME | Jill P Mesirov |
| GIVEN NAMES | Jill P |
| FAMILY NAME | Mesirov |
| SIGNATURE | MESIROV J P |
| AFFILIATIONS | Whitehead Institute for Biomedical Research |
| ORCID | 0000-0002-9755-2818 |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2001 |
| LATEST PUBLICATION YEAR | 2005 |
| H-INDEX | 0 |
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, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regu…
Initial sequencing and analysis of the human genome
The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
No prominent works on this page.
Initial sequencing and analysis of the human genome
The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
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, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regu…
Biology (2 works) · Computational biology (2 works) · Computer Science (2 works) · Gene (2 works) · Genetics (2 works) · Genome (2 works) · Bioinformatics (1 works) · Bioinformatics and Genomic Networks (1 works) · Data science (1 works) · DNA sequencing (1 works)