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Identification of Metabolic Changes in Genetically Unstable Stem Cells by Using Model Analysis of Gene Expression
Author(s) -
Vanee Niti,
Roberts Seth B.,
Riggs Marion Joe,
Rao Raj R.,
Fong Stephen S.
Publication year - 2012
Publication title -
chemistry and biodiversity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.427
H-Index - 70
eISSN - 1612-1880
pISSN - 1612-1872
DOI - 10.1002/cbdv.201100390
Subject(s) - stem cell , computational biology , identification (biology) , biology , transcriptome , microbiology and biotechnology , function (biology) , gene , adult stem cell , gene expression , cellular differentiation , genetics , botany
Stem‐cell research seeks to address many different questions related to fundamental stem‐cell function with the ultimate goal of being able to control and utilize stem cells for a broad range of therapeutic needs. While a large amount of work is focused on discovering and controlling differentiation mechanisms in stem cells, an equally interesting and important area of work is to understand the basics of stem‐cell propagation and self‐renewal. With high‐throughput genomics and transcriptomic information on hand, it is becoming possible to address some of the detailed mechanistic processes occurring in stem cells, though interpretation of these data is often difficult. In this work, stem cells with genetic abnormalities were compared to genetically normal stem cells using gene‐expression array data integrated with a large‐scale metabolic model to help interpret changes in metabolism resulting in the identification of several metabolic pathways that were different in the normal and abnormal cells.