Youfang Cao

ORCID iD
https://orcid.org/0000-0002-5880-0006
  • Country
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United States

Sources:
Youfang Cao (2016-01-24)

  • Keywords
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Stochastic reaction networks,

Sources:
Youfang Cao (2015-03-26)

Genetic circuits,

Sources:
Youfang Cao (2015-03-26)

Computational systems biology,

Sources:
Youfang Cao (2015-03-26)

Chemical master equation

Sources:
Youfang Cao (2015-03-26)

  • Websites
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http://www.youfangcao.com

Sources:
Youfang Cao (2015-03-26)

  • Email
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0000-0002-5880-0006 (2013-08-27)

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ResearcherID: A-1771-2010

Sources:
Clarivate Analytics (2013-08-27)

Biography

I have a strong interdisciplinary background in computational mathematics, biochemistry, molecular biology, and bioengineering, with in-depth experience and expertise in computational and mathematical modeling of complex biological networks and cellular systems. I have successfully developed the multi-finite buffer method for directly solving the discrete Chemical Master Equation (ACME) in my PhD thesis, which is a fundamental method for modeling stochastic biological networks in systems biology. The ACME method can solve both the steady state and time-evolving probability landscapes of realistic biological networks. It is also the first method that can optimally enumerate the state space of dCME with controlled error. I was awarded the prestigious Anthony Leggett Award, named after the Nobel laureate Anthony James Leggett, for the achievements in my thesis research. As a research assistant professor at the University of Illinois at Chicago, I carried out challenging research projects in developing novel computational methods for modeling stochastic genetic circuits and reaction networks responsible for critical cell fate determination. I have successfully carried out research in understanding the stability and efficiency control mechanism of the realistic phage lambda lysogeny-lysis cell fate determination switch network using the ACME method. I have also successfully developed a novel efficient method for estimating the rare event probabilities in biological networks. In addition, I was a key contributor in developing a dynamic model for detailed characterizations of cell geometries and mechanics, which has been successfully applied to a number of important problems, including the universal principles governing hexagon-pentagon epithelia topology in Drosophila, and the tissue homeostasis size control involving stem cell lineage in wound healing. As the leading researcher in a number of projects, I have significant experiences in challenging research and skillful communications with collaborators. After moving to the Los Alamos National Laboratory, I continue to perform these challenging research projects under the support from the Center for Nonlinear Studies (CNLS) and the Theoretical Biology and Biophysics group (T-6) at the Los Alamos National Laboratory. Furthermore, I apply the stochastic modeling methods that I have developed to the challenging problem of multiscale modeling of viral dynamics. In summary, I have a demonstrated record of productive research publications and expertise and experience in the area of computational modeling of complex biological systems, which have prepared me well to lead future challenging research projects.
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