I plan to use the K25 award at the associate professorship level to complete my transition from theoretical physics into quantitative systems biology. My immediate goal is to deepen my understanding of biology and the related chemistry. I plan to achieve it through my continuous development of a new high throughput label-free protein chip platform. This experimental route to biology has several advantages: This high throughput protein chip is very desirable in the current molecular biology research; The development has given me first-hand information on the state-of -art of experimental biology, on how the systems biology experiments are designed, and on how the data are taken and analyzed. In addition, it immediately makes use of my physics and material sciences knowledge in the designing of the instrument and of the data analysis tools. After becoming well versed in biology, I will investigate the computational side of systems biology, such as the theoretical description of the gene regulatory networks. ? ? During the award period I propose to have three intensive training rotations in yeast biology, organic chemistry, and developmental biology laboratories to learn the related modem molecular biological experimental techniques. ? ? My choice of the surface plasmon resonance technology research plan is based the following advantageous position: 1). The team led by myself has made the technical breakthroughs that put us right in the position to explore the high throughput protein chip; 2). Surface plasmon resonance technology is a most promising candidate for the high throughput protein chip, because: a). It is one of the most sensitive detection methods; b). Crude prepared protein extract can be used, which greatly simplifies the detection process; c). It can perform a real time detection, yielding vital kinetic information such as affinity for the protein-protein interaction; d). The surface plasmon resonance detection is non-label, which avoids the complicated labeling procedure as well as the risk of denaturing proteins due to labeling; e). The detection can be quantified, because the surface plasmon resonance detects the change of refractive index due to the total amount of materials on the surface. ? ? Biological models studied at the Institute for Systems Biology will be used to test and validate the label free protein chip platform during its development. Additional funds will be aggressively sought to support the project. The execution of the research plan will provide the needed opportunity to deepen my understanding of systems biology. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Mentored Quantitative Research Career Development Award (K25)
Project #
5K25HG002894-02
Application #
6793577
Study Section
Ethical, Legal, Social Implications Review Committee (GNOM)
Program Officer
Schloss, Jeffery
Project Start
2003-08-22
Project End
2008-07-31
Budget Start
2004-08-01
Budget End
2005-07-31
Support Year
2
Fiscal Year
2004
Total Cost
$185,689
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Ao, P; Galas, D; Hood, L et al. (2010) Towards predictive stochastic dynamical modeling of cancer genesis and progression. Interdiscip Sci 2:140-4
Ao, Ping (2009) Global view of bionetwork dynamics: adaptive landscape. J Genet Genomics 36:63-73
Ao, Ping; Lee, Lik Wee; Lidstrom, Mary E et al. (2008) Towards kinetic modeling of global metabolic networks: Methylobacterium extorquens AM1 growth as validation. Sheng Wu Gong Cheng Xue Bao 24:980-94
Ao, Ping; Galas, David; Hood, Leroy et al. (2008) Cancer as robust intrinsic state of endogenous molecular-cellular network shaped by evolution. Med Hypotheses 70:678-84
Ao, Ping (2007) Orders of magnitude change in phenotype rate caused by mutation. Cell Oncol 29:67-9;author reply 71-2
Kwon, Chulan; Ao, Ping; Thouless, David J (2005) Structure of stochastic dynamics near fixed points. Proc Natl Acad Sci U S A 102:13029-33
Zhu, X-M; Yin, L; Hood, L et al. (2004) Robustness, stability and efficiency of phage lambda genetic switch: dynamical structure analysis. J Bioinform Comput Biol 2:785-817