scispace - formally typeset
Author

Vamsi K. Mootha

Bio: Vamsi K. Mootha is a academic researcher at Broad Institute who has co-authored 227 publication(s) receiving 73860 citation(s). The author has an hindex of 85. Previous affiliations of Vamsi K. Mootha include Harvard University & Beth Israel Deaconess Medical Center. The author has done significant research in the topic(s): Mitochondrial DNA & Mitochondrion.

...read more

Papers
  More

Open accessJournal ArticleDOI: 10.1073/PNAS.0506580102
Abstract: 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 regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

...read more

26,320 Citations


Journal ArticleDOI: 10.1038/NG1180
01 Jul 2003-Nature Genetics
Abstract: DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1α and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

...read more

Topics: Gene expression profiling (58%), DNA microarray (54%), Gene expression (53%) ...read more

6,521 Citations


Open accessJournal ArticleDOI: 10.1016/S0092-8674(00)80611-X
Zhidan Wu1, Pere Puigserver1, Ulf Andersson2, Chen-Yu Zhang3  +7 moreInstitutions (3)
09 Jul 1999-Cell
Abstract: Mitochondrial number and function are altered in response to external stimuli in eukaryotes. While several transcription/replication factors directly regulate mitochondrial genes, the coordination of these factors into a program responsive to the environment is not understood. We show here that PGC-1, a cold-inducible coactivator of nuclear receptors, stimulates mitochondrial biogenesis and respiration in muscle cells through an induction of uncoupling protein 2 (UCP-2) and through regulation of the nuclear respiratory factors (NRFs). PGC-1 stimulates a powerful induction of NRF-1 and NRF-2 gene expression; in addition, PGC-1 binds to and coactivates the transcriptional function of NRF-1 on the promoter for mitochondrial transcription factor A (mtTFA), a direct regulator of mitochondrial DNA replication/transcription. These data elucidate a pathway that directly links external physiological stimuli to the regulation of mitochondrial biogenesis and function.

...read more

Topics: Mitochondrial biogenesis (73%), Mitochondrial DNA replication (68%), TFB1M (66%) ...read more

3,458 Citations


Open accessJournal ArticleDOI: 10.1038/NM.2307
01 Apr 2011-Nature Medicine
Abstract: Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics) We investigated whether metabolite profiles could predict the development of diabetes Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography-tandem mass spectrometry (LC-MS) Cases and controls were matched for age, body mass index and fasting glucose Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile) The results were replicated in an independent, prospective cohort These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment

...read more

Topics: Diabetes risk (71%), Aromatic amino acids (55%), Diabetes mellitus (54%) ...read more

2,169 Citations


Open accessJournal ArticleDOI: 10.1038/NATURE03441
Xiaohui Xie1, Jun Lu1, Edward J. Kulbokas1, Todd R. Golub1  +6 moreInstitutions (2)
17 Mar 2005-Nature
Abstract: Comprehensive identification of all functional elements encoded in the human genome is a fundamental need in biomedical research. Here, we present a comparative analysis of the human, mouse, rat and dog genomes to create a systematic catalogue of common regulatory motifs in promoters and 3' untranslated regions (3' UTRs). The promoter analysis yields 174 candidate motifs, including most previously known transcription-factor binding sites and 105 new motifs. The 3'-UTR analysis yields 106 motifs likely to be involved in post-transcriptional regulation. Nearly one-half are associated with microRNAs (miRNAs), leading to the discovery of many new miRNA genes and their likely target genes. Our results suggest that previous estimates of the number of human miRNA genes were low, and that miRNAs regulate at least 20% of human genes. The overall results provide a systematic view of gene regulation in the human, which will be refined as additional mammalian genomes become available.

...read more

Topics: Human genome (53%), Genome (52%), Genomics (50%)

1,909 Citations


Cited by
  More

Journal ArticleDOI: 10.1038/NPROT.2008.211
01 Jan 2009-Nature Protocols
Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

...read more

27,356 Citations


Open accessJournal ArticleDOI: 10.1073/PNAS.0506580102
Abstract: 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 regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

...read more

26,320 Citations


Open access
28 Jul 2005-
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

...read more

18,940 Citations


Open accessJournal ArticleDOI: 10.1016/J.CELL.2009.01.002
David P. Bartel1Institutions (1)
23 Jan 2009-Cell
Abstract: MicroRNAs (miRNAs) are endogenous ∼23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes.

...read more

Topics: IsomiR (58%), RISC complex (57%), Oncomir (56%) ...read more

16,392 Citations


Open accessJournal ArticleDOI: 10.1093/NAR/GKV007
Matthew E. Ritchie1, Belinda Phipson2, Di Wu3, Yifang Hu1  +4 moreInstitutions (5)
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

...read more

Topics: Microarray databases (61%), Bioconductor (51%)

13,819 Citations


Performance
Metrics

Author's H-index: 85

No. of papers from the Author in previous years
YearPapers
20221
202116
202013
201915
201815
201715

Top Attributes

Show by:

Author's top 5 most impactful journals

Cell

12 papers, 8.2K citations

Nature

10 papers, 6.1K citations

Science

9 papers, 2.8K citations

eLife

8 papers, 709 citations

Network Information
Related Authors (5)
Sarah E. Calvo

72 papers, 15.4K citations

82% related
Olga Goldberger

29 papers, 4.3K citations

81% related
Yasemin Sancak

31 papers, 13.4K citations

81% related
Hany S. Girgis

3 papers, 2.4K citations

80% related
Andrew L. Markhard

6 papers, 2.8K citations

80% related