Multimodal dynamic profiling of healthy and diseased states for future personalized health care

Clinical Pharmacology and Therapeutics

Volumn 93, Issue 1, 2013, Pages 29-32

  Mias, G I ^a   Snyder, M ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA; MOLECULAR MARKER; RNA;

ARTICLE; CANCER CELL CULTURE; DNA MICROARRAY; ENVIRONMENTAL FACTOR; GENE SEQUENCE; GENETIC VARIABILITY; GENOTYPE; HEALTH CARE; HEALTH CARE COST; HIGH THROUGHPUT SEQUENCING; HUMAN; MASS SPECTROMETRY; METABOLOMICS; PERSONALIZED MEDICINE; PRIORITY JOURNAL; PROTEOMICS; QUANTITATIVE ANALYSIS; RISK ASSESSMENT; RNA SEQUENCE; TRANSCRIPTOMICS;

COMBINED MODALITY THERAPY; DIABETES MELLITUS, TYPE 2; FORECASTING; GENOMICS; HEALTH STATUS; HUMANS; INDIVIDUALIZED MEDICINE; MALE; MIDDLE AGED; TRANSCRIPTOME;

EID: 84871268241     PISSN: 00099236     EISSN: 15326535     Source Type: Journal    
DOI: 10.1038/clpt.2012.204     Document Type: Article

References (5)

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2. Chen, R. et al. Personal omics profiling reveals dynamic molecular and medical phenotypes. Cell 148, 1293-1307 (2012).
3. Roychowdhury, S. et al. Personalized oncology through integrative highthroughput sequencing: A pilot study. Sci. Transl. Med. 3, 111ra121 (2011).
4. Ashley, E.A. et al. Clinical assessment incorporating a personal genome. Lancet 375, 1525-1535 (2010).
5. Bar-Joseph, Z., Gitter, A. & Simon, I. Studying and modelling dynamic biological processes using time-series gene expression data. Nat. Rev. Genet. 13, 552-564 (2012).