Jin Yi Wang
Affiliations: | Institute of Biophysics, Chinese Academy of Sciences, Beijing, Beijing Shi, China |
Area:
visual learning and memoryGoogle:
"Jin Wang"Mean distance: 106866
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Publications
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Chu WT, Wang J. (2018) Quantifying the Intrinsic Conformation Energy Landscape Topography of Proteins with Large-Scale Open-Closed Transition. Acs Central Science. 4: 1015-1022 |
Zhao L, Lu HP, Wang J. (2018) Exploration of Multistate Conformational Dynamics upon Ligand Binding of a Monomeric Enzyme Involved in Pyrophosphoryl Transfer. The Journal of Physical Chemistry. B |
Chu WT, Chu X, Wang J. (2017) Binding mechanism and dynamic conformational change of C subunit of PKA with different pathways. Proceedings of the National Academy of Sciences of the United States of America |
Liu C, Wang T, Bai Y, et al. (2017) Electrostatic forces govern the binding mechanism of intrinsically disordered histone chaperones. Plos One. 12: e0178405 |
Chen C, Zhang K, Feng H, et al. (2015) Multiple coupled landscapes and non-adiabatic dynamics with applications to self-activating genes. Physical Chemistry Chemical Physics : Pccp |
Jiang J, Lai Z, Wang J, et al. (2014) Signatures of the Protein Folding Pathway in Two-Dimensional Ultraviolet Spectroscopy. The Journal of Physical Chemistry Letters. 5: 1341-1346 |
Xu L, Zhang F, Zhang K, et al. (2014) The potential and flux landscape theory of ecology. Plos One. 9: e86746 |
Wang Y, Chu X, Longhi S, et al. (2013) Multiscaled exploration of coupled folding and binding of an intrinsically disordered molecular recognition element in measles virus nucleoprotein. Proceedings of the National Academy of Sciences of the United States of America. 110: E3743-52 |
Chu X, Gan L, Wang E, et al. (2013) Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition. Proceedings of the National Academy of Sciences of the United States of America. 110: E2342-51 |
Xu L, Zhang F, Wang E, et al. (2013) The potential and flux landscape, Lyapunov function and non-equilibrium thermodynamics for dynamic systems and networks with an application to signal-induced Ca2+ oscillation Nonlinearity. 26 |