MERAV: a tool for comparing gene expression across human tissues and cell types
Name
Sabatini_MERAV.pdf
Size
1.23 MB
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Adobe PDF
Checksum (MD5)
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Author(s)
Shaul, Yoav D.
Yuan, Bingbing
Thiru, Prathapan
Nutter-Upham, Andy
McCallum, Scott
Bell, George W.
Lanzkron, Carolyn
Sabatini, David
Date Issued
April 6, 2017
Journal
Nucleic Acids Research
Publisher
Oxford University Press
Citation
Shaul, Yoav D., Bingbing Yuan, Prathapan Thiru, Andy Nutter-Upham, Scott McCallum, Carolyn Lanzkron, George W. Bell, and David M. Sabatini. “MERAV: a Tool for Comparing Gene Expression Across Human Tissues and Cell Types.” Nucleic Acids Research 44, no. D1 (November 30, 2015): D560–D566.
Version
Final published version
Abstract
The oncogenic transformation of normal cells into malignant, rapidly proliferating cells requires major alterations in cell physiology. For example, the transformed cells remodel their metabolic processes to supply the additional demand for cellular building blocks. We have recently demonstrated essential metabolic processes in tumor progression through the development of a methodological analysis of gene expression. Here, we present the Metabolic gEne RApid Visualizer (MERAV, http://merav.wi.mit.edu), a web-based tool that can query a database comprising ∼4300 microarrays, representing human gene expression in normal tissues, cancer cell lines and primary tumors. MERAV has been designed as a powerful tool for whole genome analysis which offers multiple advantages: one can search many genes in parallel; compare gene expression among different tissue types as well as between normal and cancer cells; download raw data; and generate heatmaps; and finally, use its internal statistical tool. Most importantly, MERAV has been designed as a unique tool for analyzing metabolic processes as it includes matrixes specifically focused on metabolic genes and is linked to the Kyoto Encyclopedia of Genes and Genomes pathway search.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution-NonCommercial 4.0 International
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1093/nar/gkv1337
