Position: Home > Members > Junior > Ruoshi Yuan

  Ruoshi Yuan (袁若石)

  Ph.D.

 

  Supervisor : Prof. Ping AO.

 

  Office :  Room C207 Systems Biomedicine Building, Shanghai Jiao Tong  University

  Email :  rsyuan.acm06 AT gmail.com

 

Education

2016- now, Postdoc, Department of Systems Biology, Harvard Medical School.

2012-2016, Ph.D., Department of Biomedical Engineering, Shanghai Jiao Tong University.

                      Thesis title: Endogenous network hypothesis for cancer and its foundation on nonlinear stochastic dynamics.

2010-2012, M.S., Department of Computer Science, Shanghai Jiao Tong University

2008-2011, B.S., Department of Physics, Shanghai Jiao Tong University

2006-2010, B.S., ACM Honored Class, Department of Computer Science, Shanghai Jiao Tong University

 

Research

My research interest includes: stochastic and nonlinear dynamics, statistical physics, and mathematical modeling of biological phenomena.

  • We have worked out several explicit constructions of potential functions in dynamical systems with multiple fixed points, limit cycle, and even chaotic attractor.
  • Meanwhile, we developed a new stochastic interpretation for stochastic differential equations different from traditional Ito's or Stratonovich's with a clear physical meaning and a correspondence with the deterministic counterpart.
  • We construct endogenous molecular-cellular networks for various cancers. The network dynamics can be written as a set of nonlinear ordinary differential equations or stochastic differential equations. The attractors are understood as different functional states, including normal states and abnormal states such as cancer. Within this model the genesis and progression of cancer may be viewed as stochastic transitions between different attractors.
  • I create and develop a calculation platform for biological networks including automatically generated network graphs, calculation of attractors of the corresponding Boolean network, and searching stable states of ODEs with multi-CPU acceleration. The software will be put online soon.

I am concerning on how to construct the network from the insufficient and noisy biological knowledge and data. Can we find or prove the existence of a robust topological structure inside the biological network based on the current knowledge? Or more generally, is there something that organisms learn to use in the long process of evolution? I think there is; the question is how to describe them mathematically. Our network hypothesis may be a candidate.

 

Publications

1. Journal Papers:

  • Yuan, R.-S.; Zhu, X.-M.; Wang, G.-W.; Li, S.-T. & Ao, P., Cancer as robust intrinsic state shaped by evolution: a key issues review, Reports on Progress in Physics, 2017, 80 (4), 1-21
  • Yuan, R.-S.; Tang, Y. & Ao, P., On Uniqueness of "SDE Decomposition" in A-type Stochastic Integration (Comment to P. Zhou and T. Li, J. Chem. Phys. 144, 094109, 2016), The Journal of Chemical Physics, 2016, 145 (14), 147104
  • Chen, Y.-C.; Yuan, R.-S.; Ao, P.; Xu, M.-J. & Zhu, X.-M., Towards Stable Kinetics of Large Metabolic Networks: Nonequilibrium Potential Function Approach, Physical Review E, 2016, 93, 062409
  • Yuan, R.-S.; Zhu, X.-M.; Radich, J. P. & Ao, P., From Molecular Interaction to Acute Promyelocytic Leukemia: Calculating Leukemogenesis and Remission from Endogenous Molecular-Cellular Network, Scientific Reports2016, 6, 24307
  • Wang, G.-W.; Su, H.; Yu, H.-L.; Yuan, R.-S.; Zhu, X.-M. & Ao, P., Endogenous Network States Predict Gain or Loss of Functions for Genetic Mutations in Hepatocellular Carcinoma, Journal of the Royal Society Interface, 2016, 13, 20151115
  • Yuan, R.-S.; Ma, S.-F.; Zhu, X.-M.; Li, J.; Liang, Y.-H.; Liu, T.; Zhu, Y.-X.; Zhang, B.-B.; Tan, S.; Guo, H.-J. ; Guan, S.-G.; Ao, P. & Zhou G.-Q., Core Level Regulatory Network of Osteoblast as Molecular Mechanism for Osteoporosis and Treatment, Oncotarget, 2016, 6923
  • Tang, Y.; Yuan, R.-S. & Ao, P., Anomalous Free Energy Changes Induced by Topology, Physical Review E2015, 92, 062129
  • Tang, Y.; Yuan, R.-S.; Chen, J.-H. & Ao, P., Work Relations Connecting Nonequilibrium Steady States without Detailed Balance, Physical Review E201591, 042108
  • Zhu, X.-M.; Yuan, R.-S.; Hood, L. & Ao, P., Endogenous Molecular-Cellular Hierarchical Modeling of Prostate Carcinogenesis Uncovers Robust Structure, Progress in Biophysics and Molecular Biology2015, 117(1): 30-42  (Corresponding author)
  • Tang, Y.; Yuan, R.-S.; Chen, J.-H. & Ao, P., Controlling Symmetry-Breaking States by a Hidden Quantity in Multiplicative Noise, Physical Review E201490, 052121
  • Tang, Y.; Yuan, R.-S. & Ao, P., Summing over Trajectories of Stochastic Dynamics with Multiplicative Noise, The Journal of Chemical Physics, 2014, 141 (4), 044125
  • Tang, Y.; Yuan, R.-S. & Ao, P., Nonequilibrium Work Relation Beyond the Boltzmann-Gibbs Distribution, Physical Review E, 2014, 89, 062112
  • Hu, J.; Zhu, X.-M.; Wang, X.-A.; Yuan, R.-S.; Zheng, W.; Xu, M.-J. & Ao, P., Two Programmed Replicative Lifespans of Saccharomyces cerevisiae Formed by Endogenous Molecular-Cellular Network, Journal of Theoretical Biology2014, in press
  • Ma, Y.-A.; Tan, Q.-J.; Yuan, R.-S.; Yuan, B. & Ao, P., Potential Function in a Continuous Dissipative Chaotic System: Decomposition Scheme and Role of Strange Attractor, International Journal of Bifurcation and Chaos2014, 24 (2), 1450015 (Arxiv preprint arXiv:1208.1654)
  • Yuan, R.-S.; Ma, Y.-A.; Yuan, B. & Ao, P., Lyapunov Function as Potential Function: A Dynamical Equivalence, Chinese Physics B. 2014, 23 (1): 010505 (Arxiv preprint arXiv:1012.2721)
  • Yuan, R.-S.; Wang, X.-A.; Ma, Y.-A.; Yuan, B. & Ao, P., Exploring a Noisy van der Pol Type Oscillator with a Stochastic Approach, Physical Review E, 2013, 87 (6), 062109 (Arxiv preprint arXiv:1210.7284)
  • Tang, Y.; Yuan, R.-S. & Ma, Y.-A., Dynamical Behaviors Determined by the Lyapunov Function in Competitive Lotka-Volterra Systems, Physical Review E, 2013, 87 (1), 012708 (Co-first author, Arxiv preprint arXiv:1210.7662)
  • Yuan, R.-S. & Ao, P., Beyond Itô versus Stratonovich, Journal of Statistical Mechanics: Theory and Experiment2012, P07010 (Arxiv preprint arXiv:1203.6600)
  • Shi, J.-H.; Chen, T.-Q.; Yuan, R.-S.; Yuan, B. & Ao, P., Relation of a New Interpretation of Stochastic Differential Equations to Ito Process, Journal of Statistical Physics2012, 148 (3), 579-590 (Arxiv preprint arXiv:1111.2987)
  • Sun, T.-Z.; Yuan, R.-S.; Xu, W.; Zhu, F. & Shen, P.-P., Exploring a Minimal Two-component p53 Model, Physical Biology, 2010, 7 (3), 036008

2. Conference:

3. Preprints:

 

Talks and Posters

Research Experience

2014-2015, Visiting Scholar, Department of Systems Biology, Harvard Medical School, advised by Prof. Johan Paulsson.

2009-present, Research Assistant, Systems Biology Lab, advised by Prof. Ping Ao.

2009-2012, Research Assistant, Biocomputing and Bioinformatics Lab, advised by Prof. Bo Yuan.

2009, Research Assistant, Microsoft Research Asia, advised by Researcher Bin Gao.

2008-2009, Research Assistant, APEX Lab, advised by Prof. Yong Yu.

 

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