title: Identification of metabolic changes in genetically unstable stem cells by using model analysis of gene expression.
abstract: 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.
authors.affiliation: VCU Life Sciences, Virginia Commonwealth University, 601 W Main Street, P.O. Box 843068, Richmond, VA 23220, USA.
authors.forename: Niti
authors.initials: N
authors.lastname: Vanee
authors.forename: Seth B
authors.initials: SB
authors.lastname: Roberts
authors.forename: Marion Joe
authors.initials: MJ
authors.lastname: Riggs
authors.forename: Raj R
authors.initials: RR
authors.lastname: Rao
authors.forename: Stephen S
authors.initials: SS
authors.lastname: Fong
mesh_terms: D000465:Algorithms; D002454:Cell Differentiation; D005786:Gene Expression Regulation; D023281:Genomics; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis; D013234:Stem Cells / Q000166:cytology / Q000378:metabolism*; D059467:Transcriptome