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Nathan D. Price

• Sam E. and Kathleen Henry Postdoctoral Fellowship, American Cancer Society, 2005-2007
• Tomorrow′s PIs, Genome Technology, 2007
• Howard Temin Pathway to Independence in Cancer Research Award, National Cancer Institute, 2008-2012
• CAREER Award, National Science Foundation, 2009

Computational and Systems Biology

Our lab works in the emerging field of systems biology – the intersection of high-throughput experimental biology with large-scale computational modeling to drive biological discovery. Within the context of a computational model, various data types interact in precisely defined ways such that predictions of cellular behavior can be made under novel conditions or perturbations. Failure modes of computational models point towards gaps in understanding and lead to directed lines of questioning from which understanding of the cell's workings can be increased in a systematic fashion. Constructing and revising computational models based on data constitutes a powerful iterative model building approach that lies at the heart of systems biology.

Complex Biomolecular Networks

We are interested in the structure, dynamics, and information-processing capabilities of complex biomolecular networks. These networks can be interrogated using high-throughput measurement technologies (genomics, transcriptomics, proteomics, metabolomics, CHIP-chip, etc.) and computational network models can be built to explain and even predict the outcome of such experiments. These network models can be of many types, including genome-scale biochemical networks with known stoichiometries, statistical inference models, kinetic models, discrete dynamic networks, probabilistic networks and so forth. Predictive cell-scale models will enable synthetic biology and cellular engineering by allowing for the rationale design of cells as an engineering problem. These engineering designs can have applications to many important challenges including for bioenergy and medicine.

Systems Biology of Cancer

The systems approach to medicine derives from a simple idea – the difference between normal and diseased cells lies in one or more disease-perturbed network. These disease-perturbed networks have altered patterns of expression in genes and proteins, and these altered patterns necessarily result in altered molecular fingerprints that can be measured. Cancer is an important and well-suited disease to study with a systems approach. We are interested in integrating high-throughput data to construct computational models of complex biomolecular processes in cancer, including brain cancer (glioblastoma), ovarian cancer, and gastro-intestinal cancers. For each of these cancers, our lab has ongoing collaborations with clinicians and cancer biologists. The aims of this research are to 1) identify molecular signatures for cancer diagnosis and treatment selection, and 2) generate predictive cancer network models that will link observed molecular signatures to underlying causal perturbations and identify therapeutic targets.

Model-guided Cellular Engineering

We are interested in using genome-scale computational models to guide modification of organisms to accomplish engineering goals. In particular, we will focus on reconstructing genome-scale metabolic and regulatory networks to guide engineering of micro-organisms to convert feedstocks to biofuels, as part of an emerging large-scale effort on campus in bioenergy research. To accomplish this, it is necessary to model how the cell will respond as an integrated system under given environments with novel perturbations so that our engineering objective (i.e. biofuel production) is aligned with the "objective" of the organism in its given environment (i.e. cell growth). Reliable predictive models hold the promise of significantly increasing our ability to rationally design and modify biological systems.

Selected Publications

L.B. Edelman, S. Chandrasekaran, and N.D. Price, "Systems biology of embryogenesis," Reproduction, Fertility, and Development, (accepted, 2009).

L.B. Edelman, G. Toia, D. Geman, W. Zhang, and N.D. Price, "Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases," BMC Genomics, (in revision, 2009).

L.B. Edelman, J.A. Eddy, and N.D. Price, "In silico models of cancer," Wiley Interdisciplinary Reviews: Systems Biology and Medicine, (accepted, 2009).

D. Hwang, I.Y. Lee, H. Yoo, N. Gehlenborg, J.H. Cho, B. Petritis, D. Baxter, R. Pitstick, R. Young, D. Spicer, N.D. Price, J. Hohmann, S.J. DeArmond, G.A. Carlson, L. Hood, " A Systems Approach to Prion Disesase," Molecular Systems Biology, 5, 252 (2009).

J.A. Eddy, and N.D. Price, "Biological data integration and model building," Encyclopedia of Complexity and Systems Science, ( R.A. Meyers, editor) Springer, (in press, 2009)

H.P. Blaschek, T. Ezeji, and N.D. Price, " Present and future possibilities for the deconstruction and utilization of lignocellulosic biomass," Handbook of Bioenergy, (in press, 2009)

N.D. Price, L.B. Edelman, I. Lee, H.Yoo, D. Hwang, G. Carlson, D.J. Galas, J.R. Heath, and L. Hood, "Systems biology and systems medicine," Genomic and Personalized Medicine: From Principles to Practice (Ginsburg, G. and Willard, H., editors). Elsevier,1, 74-85 (2009).

M. Nykter, N.D. Price, A. Larjo, T. Aho, M. Aldana, S.A. Kauffman, L. Hood, O. Yli-Harja, and I. Shmulevich, "Critical Boolean networks exhibit maximal information diversity in structure-dynamics relationships," Physical Review Letters, 100, 058702 (2008).

M. Nykter, N.D. Price, M. Aldana, S. Ramsey, S.A. Kauffman, L. Hood, O. Yli-Harja, and I. Shmulevich, "Gene expression dynamics in the macrophage exhibit criticality," Proceedings of the National Academy of Sciences USA, 105, 1897-1900 (2008).

N.D.Price, G. Foltz, A. Madan, L. Hood, and Q. Tian, "Systems biology and cancer stem cells," Journal of Cellular and Molecular Medicine, 12, 97-110 (2008).

N.D. Price and I. Shmulevich, "Biochemical and statistical network models for systems biology," Current Opinion in Biotechnology, 18 365-370 (2007).

N.D. Price, J. Trent, A.K. El-Naggar, D. Cogdell, E. Taylor, K.K. Hunt, R.E. Pollock, L. Hood, I. Shmulevich and W. Zhang, "Highly accurate two-gene classifier for differentiating gastrointestinal stromal tumors and leiomyosarcomas," Proceedings of the National Academy of Sciences USA, 104, 3414-3419 (2007).

E.J. Gianchandani, J.A. Papin, N.D. Price, A. Joyce, and B.O. Palsson, "Matrix formalism for representing functional states of transcriptional regulatory networks," PLoS Computational Biology, 2, e101 (2006). Cover Article

N.D. Price, I. Thiele and B.O. Palsson, "Candidate states of Helicobacter pylori's genome-scale metabolic network upon application of “loop law” thermodynamic constraints," Biophysical Journal, 90, 3919-3928 (2006).

T.E. Allen, N.D. Price, A. Joyce, and B.O. Palsson, "Long-range patterns in prokaryotic genome sequences indicate significant chromosomal organization," PLoS Computational Biology, 2, e2 (2006). Cover Article

I. Thiele, T.D. Vo, N.D. Price and B.O. Palsson, " Expanded metabolic reconstruction of Helicobacter pylori (iIT341 GSM/GPR): an in silico genome-scale characterization of single- and double-deletion mutants," Journal of Bacteriology, 187, 5818-5830 (2005).

I. Thiele, N.D. Price, T.D. Vo and B.O. Palsson, "Candidate metabolic network states in human mitochondria: impact of diabetes, ischemia, and diet," Journal of Biological Chemistry, 280, 11683-11695, (2005).

N.D. Price, J.L. Reed and B.O. Palsson, "Genome-scale models of microbial cells: Evaluating the consequences of constraints," Nature Reviews Microbiology, 2, 886-897, (2004).

N.D. Price, J. Schellenberger and B.O. Palsson, "Uniform sampling of steady-state flux spaces: Means to design experiments and to interpret enzymopathies," Biophysical Journal, 87, 2172-2186 (2004).

Department of Chemical & Biomolecular Engineering | University of Illinois at Urbana-Champaign
114 Roger Adams Laboratory, MC 712 | 600 South Mathews Avenue | Urbana, IL 61801
217/333-3640 | FAX 217/333-5052