Louis Tao, Ph.D.

Research Fellow
Center for Bioinformatics
Life Science College
Peking University

Contact

E-mail:
Tel: +86 10 6275 5206

Address

Room 606
New Life Science Building
Peking University
Beijing, P. R. China,
100871

Previous Experience

• 2008-Present Center for Bioinformatics, Peking University
• 2003-2007 Assistant Professor, New Jersey Institute of Technology
• 2000-2003 Associate Research Scientist, New York University
• 1997-2000 NSF Postdoctoral fellow, Columbia Unversity
• 1995-1997 Postdoctoral Research Assistant, Cambridge University

Courses Taught

• Methods in Bioinformatics
• Mathematical Modeling and System Biology

Research Interests

• Mathematical modeling of sensory systems
• Dimensional-reduction techniques applied to neuronal networks
• Kinetic theory of neuronal networks
• Mathematical analysis of neural systems imaging data

Publications

• Tao, L., Praissman, J., and Sornborger, A.T. Improved dimensionally-reduced visual cortical network using stochastic noise modeling, in revision at J. Comput. Neurosci.
• Tao, L., Lauderdale, J.D. and Sornborger, A.T., Mapping functional connectivity between neuronal ensembles with larval zebrafish transgenic for a ratiometric calcium indicator, Front Neural Circuits. 2011 Feb 22;5:2.
• Carceras, M.J., Carrillo, J.A., and Tao, L., A numerical solver for a nonlinear Fokker-Planck equation representation of neuronal network dynamics, accepted for publication in J. Comput. Phys
• Tao, L. and Sornborger, Dimensionally-reduced visual cortical network model predicts network response and connects system- and cellular-level descriptions, J. Comput. Neurosci., 28, 91-106 (2010).
• Rangan, A.V., Tao, L., Kovacic, G. and Cai, D., Large-scale computational modeling of the primary visual cortex, in Coherent Behavior in Neuronal Networks, edited by Josic, K. et al., Springer Ser. Comput. Neurosci., Vol. 3, Springer-Verlag (2009)
• Kovacic, G., Tao, L., Rangan, A.V., and Cai, D., Fokker-Planck description of conductance-based integrate-and-fire neuronal networks, Phys. Rev. E, 80, 021904 (2009).
• Zhao, M., Chen, X., Gao, G., Tao, L., and Wei, L., RLEdb: a database of rate-limiting enzymes and their regulation in human, rat, mouse, yeast and E. coli, Cell Res. 16, 793-5 (2009).
• Gao, G., Li, J.-T., Kong, L., Tao, L. and Wei, L., Human herpesvirus miRNAs statistically preferentially target host genes involved in cell signaling and adhesion/junction pathways, Cell Res. 19, 665-667 (2009).
• Rangan, A.V., Tao, L., Kovacic, G., and Cai, D. Multi-scale modeling of the primary visual cortex, IEEE Eng. Med. Biol., 28, 19-24 (2009).
• Kovacic, G., Tao, L., Cai, D., and Shelley, M.J. Theoretical analysis of reverse-time correlation for idealized tuning dynamics, J. Comput. Neurosci. 25, 401-438 (2008).
• Rangan, A., Cai, D., and Tao, L., Numerical method for solving moment equations in kinetic theory of neuronal networks, J. Comput. Phys. 221, 781-798 (2007).
• Tao, L., Cai, D., McLaughlin, D., Shelley, M., and Shapley, R., Orientation selectivity in visual cortex by fluctuation-controlled criticality, Proc. Natl. Acad. Sci. USA 103, 12911-12916 (2006).
• Cai, D.,Tao, L., Rangan, A., and McLaughlin, D., Kinetic theory for neuronal network dynamics, Comm. Math. Sci. 4, 97-127 (2006).
• Cai, D., Tao, L., and McLaughlin, D., An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information, Proc. Natl. Acad. Sci. USA 101, 14288-14293 (2004).
• Cai, D., Tao, L., Shelley, M., and McLaughlin, D., An effective kinetic representation of fluctuation-driven neuronal networks with application to Simple and Complex cells in visual cortex, Proc. Natl. Acad. Sci. USA 101, 7757-7762 (2004).
• Tao, L., Shelley, M.J., McLaughlin, D.W., and Shapley, R.M., An egalitarian network model for the emergence of Simple and Complex cells in visual cortex, Proc. Natl. Acad. Sci. USA 101, 366-371 (2004).
• Shelley, M.J., and Tao, L., Efficient and accurate time-stepping schemes for integrate-and-fire neuronal networks, J. Comput. Neurosci. 11, 111-119 (2001).