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Identifying gene expression modules that define human cell fates.
Germanguz, I; Listgarten, J; Cinkornpumin, J; Solomon, A; Gaeta, X; Lowry, W E.
Afiliación
  • Germanguz I; Molecular, Cell and Developmental Biology, UCLA, United States; Eli and Edythe Broad Center for Regenerative Medicine, UCLA, United States.
  • Listgarten J; Microsoft Research, United States.
  • Cinkornpumin J; Molecular, Cell and Developmental Biology, UCLA, United States; Eli and Edythe Broad Center for Regenerative Medicine, UCLA, United States.
  • Solomon A; Molecular, Cell and Developmental Biology, UCLA, United States; Eli and Edythe Broad Center for Regenerative Medicine, UCLA, United States.
  • Gaeta X; Molecular, Cell and Developmental Biology, UCLA, United States; Eli and Edythe Broad Center for Regenerative Medicine, UCLA, United States.
  • Lowry WE; Molecular, Cell and Developmental Biology, UCLA, United States; Eli and Edythe Broad Center for Regenerative Medicine, UCLA, United States; Molecular Biology Institute, UCLA, United States. Electronic address: blowry@ucla.edu.
Stem Cell Res ; 16(3): 712-24, 2016 05.
Article en En | MEDLINE | ID: mdl-27108395
ABSTRACT
Using a compendium of cell-state-specific gene expression data, we identified genes that uniquely define cell states, including those thought to represent various developmental stages. Our analysis sheds light on human cell fate through the identification of core genes that are altered over several developmental milestones, and across regional specification. Here we present cell-type specific gene expression data for 17 distinct cell states and demonstrate that these modules of genes can in fact define cell fate. Lastly, we introduce a web-based database to disseminate the results.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Stem Cell Res Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Algoritmos Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Stem Cell Res Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos