Linking physiology and transcriptional profiles by quantitative predictive models

Biotechnology and Bioengineering

Volumn 98, Issue 1, 2007, Pages 252-260

  Misra, Jatin ^a   Alevizos, Ilias ^a,b   Hwang, Daehee ^c   Stephanopoulos, George ^a   Stephanopoulos, Gregory ^a  

^a Massachusetts Institute of Technology   (United States)

^b UNIVERSITY OF PADOVA   (Italy)

^c INSTITUTE FOR SYSTEMS BIOLOGY   (United States)

Author keywords

Insulin resistance; Partial least squares

Indexed keywords

GENES; MATHEMATICAL MODELS; MICROARRAYS; REGRESSION ANALYSIS; SIGNAL TO NOISE RATIO; YEAST;

INSULIN RESISTANCE; LEPTIN LEVELS; PARTIAL LEAST SQUARES;

BIOTECHNOLOGY;

INSULIN; LEPTIN;

ANIMAL MODEL; ARTICLE; CONTROLLED STUDY; DNA MICROARRAY; GENE IDENTIFICATION; GROWTH RATE; INSULIN RESISTANCE; LIPID DIET; MATHEMATICAL MODEL; MOUSE; NONHUMAN; OBESITY; PARTIAL LEAST SQUARES REGRESSION; SIGNAL NOISE RATIO;

ALGORITHMS; ANIMALS; GENE EXPRESSION PROFILING; MICE; MICE, INBRED C57BL; MODELS, BIOLOGICAL; OBESITY; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEOME; SIGNAL TRANSDUCTION; TRANSCRIPTION FACTORS;

MUS;

EID: 34548236521     PISSN: 00063592     EISSN: 10970290     Source Type: Journal    
DOI: 10.1002/bit.21540     Document Type: Article

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