Title: De Novo Protein Structure  Prediction  from  low  resolution  protein
density map


Abstract
Protein structure prediction is also known as the  protein  folding  problem
that attracts the  scientists  from  many  disciplines.  Generally,  protein
structure prediction  uses  the  amino  acid  sequence  information  of  the
protein to build possible conformations and searches for the  one  that  has
the global minimum energy. However,  current  structure  prediction  methods
are still far from being mature. We have been investigating the  problem  of
combining the structure  prediction  methods  with  geometrical  constraints
that can be obtained from the low resolution 3-dimensional image of  protein
density that can be generated with the electron  cryo-microscopy  technique.
We have developed a method to predict the possible 3-dimensional  structures
of the protein using the  constraints  extracted  from  the  low  resolution
density map. In this talk, I will summarize our previous  work  and  discuss
some of the ongoing work after joining ODU.

Bio:
Dr. He obtained her B.S. degree in mathematics from  Jilin  University,  and
M.S. degree in mathematics from Mew Mexico State University. She  worked  in
the area of 3-dimensional reconstruction and analysis  of  virus  structures
at Baylor  College  of  Medicine  from  which  she  obtained  her  Ph.D.  in
Structural and Computational Biology  and  Molecular  Biophysics.  Currently
she is an Associate Professor at the Department of Computer Science.