This project targets the challenge of connecting genetics theory with multi-scale physiological models, to address and understand physiological genomics in a population context. Many challenges in personalized medicine reflect a lack of understanding of the genotype-to-phenotype (GP) map (see Figure 1.1), i.e. the aggregated phenotypic effects across different length and time scales of different constellations of genetic variation (genotypes). Our approach is motivated by the fact that understanding the GP map for a complex trait is likely to require mechanistic model descriptions of the phenotypic effects of genetic variation, i.e. advanced multiseale physiological models with an explicit link to genetic information. We use the term causally cohesive genotype-phenotype models for models describing how genetic variation manifests in phenotypic variation at various systemic levels up to the tissue, organ and whole-organism level [19]. Causally cohesive genotype phenotype models are in silico representations that emerge from a composite mapping, first from genotypes to model parameters, and second from models to phenotypes, which may in turn be parameters in overlying model structures. (See Figure 1.1.) This approach makes it possible to address a whole range of complex phenomena, like genetic dominance, epistasis, penetrance, plelotropy, cryptic variation and genotype/environment interactions in ways that are beyond reach of classical statistical approaches [16-22]. In combination with the very advanced models to be developed in this project, this approach will provide novel and important information about the relationships between genetic variation and complex diseases.
| Williams, Nakeya D; Mehlsen, Jesper; Tran, Hien T et al. (2018) An optimal control approach for blood pressure regulation during head-up tilt. Biol Cybern : |
| Olsen, Christian Haargaard; Ottesen, Johnny T; Smith, Ralph C et al. (2018) Parameter subset selection techniques for problems in mathematical biology. Biol Cybern : |
| Wright, Peter T; Bhogal, Navneet K; Diakonov, Ivan et al. (2018) Cardiomyocyte Membrane Structure and cAMP Compartmentation Produce Anatomical Variation in ?2AR-cAMP Responsiveness in Murine Hearts. Cell Rep 23:459-469 |
| Ciocanel, Maria-Veronica; Docken, Steffen S; Gasper, Rebecca E et al. (2018) Cardiovascular regulation in response to multiple hemorrhages: analysis and parameter estimation. Biol Cybern : |
| Qureshi, M Umar; Colebank, Mitchel J; Schreier, David A et al. (2018) Characteristic impedance: frequency or time domain approach? Physiol Meas 39:014004 |
| Herum, Kate M; Choppe, Jonas; Kumar, Aditya et al. (2017) Mechanical regulation of cardiac fibroblast profibrotic phenotypes. Mol Biol Cell 28:1871-1882 |
| McClymont, Darryl; Teh, Irvin; Carruth, Eric et al. (2017) Evaluation of non-Gaussian diffusion in cardiac MRI. Magn Reson Med 78:1174-1186 |
| Sturdy, Jacob; Ottesen, Johnny T; Olufsen, Mette S (2017) Modeling the differentiation of A- and C-type baroreceptor firing patterns. J Comput Neurosci 42:11-30 |
| Tran, Kenneth; Han, June-Chiew; Taberner, Andrew J et al. (2016) Myocardial energetics is not compromised during compensated hypertrophy in the Dahl salt-sensitive rat model of hypertension. Am J Physiol Heart Circ Physiol 311:H563-71 |
| Lee, Pilhwa; Wolgemuth, Charles W (2016) Physical Mechanisms of Cancer in the Transition to Metastasis. Biophys J 111:256-66 |
Showing the most recent 10 out of 116 publications
