Abstract
Understanding the relationships between human genetic factors, the risks of developing major diseases and the molecular basis of drug efficacy and toxicity is a fundamental problem in modern biology. Predicting biological outcomes on the basis of genomic data is a major challenge because of the interactions of specific genetic profiles with numerous environmental factors that may conditionally influence disease risks in a nonlinear fashion. 'Global' systems biology attempts to integrate multivariate biological information to better understand the interaction of genes with the environment. The measurement and modeling of such diverse information sets is difficult at the analytical and bioinformatic modeling levels. Highly complex animals such as humans can be considered 'superorganisms' with an internal ecosystem of diverse symbiotic microbiota and parasites that have interactive metabolic processes. We now need novel approaches to measure and model metabolic compartments in interacting cell types and genomes that are connected by cometabolic processes in symbiotic mammalian systems.
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Acknowledgements
We thank the Biotechnology and Biological Science Research Council, Engineering and Physical Sciences Research Council, The Wellcome Trust and the National Institutes of Health for funding this and related work. We also thank Paul Elliot and James Scott, Yueurg Utzinger and Burt Singer, Jeremy Everett and Felicity Nicholson for their helpful comments and discussion on this work and related subjects.
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Nicholson, J., Holmes, E., Lindon, J. et al. The challenges of modeling mammalian biocomplexity. Nat Biotechnol 22, 1268–1274 (2004). https://doi.org/10.1038/nbt1015
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DOI: https://doi.org/10.1038/nbt1015
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