Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2006:2:52.
doi: 10.1038/msb4100095. Epub 2006 Oct 3.

Global systems biology, personalized medicine and molecular epidemiology

Jeremy K Nicholson
Editorial

Global systems biology, personalized medicine and molecular epidemiology

Jeremy K Nicholson. Mol Syst Biol. 2006.
No abstract available

PubMed Disclaimer

Figures

Figure 1
Figure 1
Relationships between systems biology, personalized healthcare and molecular epidemiology (dotted lines indicate indirect connections or influences).
Figure 2
Figure 2
Pharmaco-metabonomic modelling procedure: spectroscopic data on pre-dose metabolic fingerprints (X matrix) from biofluids such as urine and plasma are statistically linked to outcome (quantitative toxicity (Y1) drug metabolism (Y2) matrixes) of a drug intervention via multivariate statistics such as partial least squares methods. Typically, 20–50% of all data is used in the training set construction. The predictive power of the models is then tested using a test set or a cross-validation set to assess model robustness. It is also possible as an additional test to avoid overfitting of data, to deliberately permute the training set matrixes to induce a false model that should have a very low predictive capability.
See this image and copyright information in PMC

References

    1. Brugman S, Klatter FA, Visser JTJ, Wildeboer-Veloo ACM, Harmsen HJM, Rozing J, Bos NA (2006) Antibiotic treatment partially protects against type 1 diabetes in the Bio-Breeding diabetes-prone rat. Is the gut microflora involved in the development of type 1 diabetes. Diabetologia 49: 2105–2108 - PubMed
    1. Cavalli-Sforza LL, Feldman MW (2003) The application of molecular genetic approaches to the study of human evolution. Nat Genet 33: 266–275 - PubMed
    1. Clayton TA, Lindon JC, Antti H, Charuel C, Hanton G, Provost JP, Le Net JL, Baker D, Walley RJ, Everett JE, Nicholson JK (2006) Pharmaco-metabonomic phenotyping and personalised drug treatment. Nature 440: 1073–1077 - PubMed
    1. Dumas ME, Barton RH, Toye A, Cloarec O, Blancher C, Rothwell A, Fearnside J, Tatoud R, Blanc V, Lindon JC, Mitchell S, Holmes E, McCarthy MI, Scott J, Gauguier D, Nicholson JK (2006a) Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin resistant mice. Proc Natl Acad Sci USA 103: 12511–12516 - PMC - PubMed
    1. Dumas ME, Maibaum EC, Teague C, Ueshima H, Zhou BF, Lindon JC, Nicholson JK, Stamler J, Elliott P, Chan Q, Holmes E (2006b) Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics in large scale epidemiological studies. Anal Chem 78: 2199–2208 - PMC - PubMed

Publication types