Ph.D. Program in Structural and
Computational Biology and
Molecular Biophysics

Patrick Barth

Patrick Barth

Baylor College of Medicine

Department: Pharmacology, Biochemistry & Molecular Biology
Address: One Baylor Plaza
Houston, Texas 77030
Phone: 713-798-8508
Fax: 713-798-3145
Email: patrickb@bcm.edu
Web:

Education

B.S. Physics and Chemistry (University of Paris VI - France) (1994)
Master, Bioinorganic Chemistry (University of Paris XI Orsay - France (1996)
Ph.D., Biophysics (University of Paris XI Orsay / CEA Saclay - France) (2000)
UC Berkeley; University of Washington

Honors

HONORS
2000: PhD title with highest honors
1996: Master of Bioinorganic Chemistry with highest honors
1995: Bachelor honor degree with highest honors
1994: Bachelor degree with highest honors

FELLOWSHIPS AND AWARDS
1999- 2000: CNRS doctoral research fellowship
1997- 1999: CEA doctoral research fellowship
1995- 1996: Ministry of Education fellowship

Research Topic

Signaling mechanisms across biological membranes by computational modeling, design and experimental biophysics

Research Description

My lab is interested in how signals are faithfully transmitted across biological membranes. How do receptors sense and respond to diverse ligands? How do receptors communicate with each other in the membrane? How do receptor-receptor interactions modulate signaling? Can we recapitulate these properties by design and rewire signaling pathways?

We address these questions using a combination of molecular modeling, bioinformatics and experimental approaches to model, design and reprogram receptor/ligand interaction networks. Our long-term goal is to deconstruct the complex function and quantitatively describe the basic principles underlying these signaling networks.

We have developed an ensemble of physical models and computational methods to model and design receptor structures and interactions. We have also combined experimental data with modeling techniques to model specific functional states of receptors. Finally, we have cross-validated our predictions experimentally. This interdisciplinary approach is essential to our research and we welcome students and postdocs with computational and experimental backgrounds to continue fostering a very collaborative environment in the lab.

Selected Publications

Lab Members

Lab Photos

Last edited on: November 06, 2009