Systems biology approaches to understanding stem cell fate choice

IET Systems Biology

Volumn 4, Issue 1, 2010, Pages 1-11

  Peltier, J ^a   Schaffer, D V ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b University of California at Berkeley   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL TYPES; COMPLEX SIGNAL; EMERGENT BEHAVIOURS; ENGINEERING CELLS; EX-VIVO; EXPERIMENTAL APPROACHES; FEED-BACK LOOP; FEEDFORWARD LOOPS; GENE REGULATION NETWORK; LARGE DATASETS; MANAGED NETWORKS; MATHEMATICAL FORMALISM; PARTIAL LEAST-SQUARES REGRESSION; PRINCIPAL COMPONENTS; PRINCIPAL COMPONENTS ANALYSIS; REGULATORY NETWORK; SIGNALLING PATHWAYS; STATISTICAL ANALYSIS; STEM CELL; STEM CELL EXPANSION; SYSTEMS BIOLOGY; THERAPEUTIC POTENTIALS; TISSUE REPAIR;

BAYESIAN NETWORKS; BIOLOGY; COMPUTER SIMULATION; INFERENCE ENGINES; LAWS AND LEGISLATION; PRINCIPAL COMPONENT ANALYSIS; SIGNAL TRANSDUCTION; STOCHASTIC MODELS; TISSUE ENGINEERING;

STEM CELLS;

HARNESS;

PROTEOME;

ALGORITHM; ANIMAL; BIOLOGICAL MODEL; CELL DIFFERENTIATION; COMPUTER SIMULATION; CYTOLOGY; HUMAN; METABOLISM; PHYSIOLOGY; REVIEW; STEM CELL; SYSTEMS BIOLOGY;

ALGORITHMS; ANIMALS; CELL DIFFERENTIATION; COMPUTER SIMULATION; HUMANS; MODELS, BIOLOGICAL; PROTEOME; STEM CELLS; SYSTEMS BIOLOGY;

EID: 75649144076     PISSN: 17518849     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-syb.2009.0011     Document Type: Article

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