M. Betancourt

发表

Pair potentials for protein folding: Choice of reference states and sensitivity of predicted native states to variations in the interaction schemes

D. Thirumalai, M. Betancourt, 2008, Protein science : a publication of the Protein Society.

Local propensities and statistical potentials of backbone dihedral angles in proteins.

J. Skolnick, M. Betancourt, 2004, Journal of molecular biology.

Ab initio protein structure prediction via a combination of threading, lattice folding, clustering, and structure refinement

J. Skolnick, A. Kolinski, D. Kihara, 2001, Proteins.

Virtual atom representation of hydrogen bonds in minimal off-lattice models of alpha helices: effect on stability, cooperativity and kinetics.

D. Thirumalai, M. Betancourt, D. Klimov, 1998, Folding & design.

Finding the needle in a haystack: educing native folds from ambiguous ab initio protein structure predictions

J. Skolnick, M. Betancourt, 2001 .

Universal similarity measure for comparing protein structures.

J Skolnick, M R Betancourt, J. Skolnick, 2001, Biopolymers.

Modeling bond correlations in denatured proteins and polypeptides

M. Betancourt, 2016, Biopolymers.

Dynamics Study of the OH + O2 Branching Atmospheric Reaction. 3. Dissociation in Collisions of Vibrationally Excited Reactants

M. Betancourt, A. Varandas, P. Caridade, 2001 .

Finding the needle in a haystack: educing native folds from ambiguous ab initio protein structure predictions

Jeffrey Skolnick, Marcos R. Betancourt, J. Skolnick, 2001, J. Comput. Chem..

Exploring the kinetic requirements for enhancement of protein folding rates in the GroEL cavity.

D Thirumalai, M R Betancourt, D. Thirumalai, 1999, Journal of molecular biology.

D Thirumalai schemes sensitivity of predicted native states to variations in the interaction Pair potentials for protein folding : choice of reference states and

D. Thirumalai, M. Betancourt, 1999 .

KINETICS OF PROTEINLIKE MODELS : THE ENERGY LANDSCAPE FACTORS THAT DETERMINE FOLDING

J. Onuchic, M. Betancourt, 1995 .

Generalized comparative modeling (GENECOMP): A combination of sequence comparison, threading, and lattice modeling for protein structure prediction and refinement

P Rotkiewicz, A Kolinski, J Skolnick, 2001, Proteins.

Generalize dComparativ eModelin g(GENECOMP) :A Combinatio no fSequenc eComparison ,Threading ,and Lattic eModelin gfo rProtei nStructur ePredictio nand Refinement

A. Kolinski, D. Kihara, P. Rotkiewicz, 2001 .

Another look at the conditions for the extraction of protein knowledge‐based potentials

M. Betancourt, Marcos R Betancourt, 2009, Proteins.

Optimization of Monte Carlo trial moves for protein simulations.

M. Betancourt, Marcos R. Betancourt, 2011, The Journal of chemical physics.

Smoothing the landscapes of protein folding: Insights from a minimal model

M. Betancourt, 1998 .

Efficient Monte Carlo trial moves for polypeptide simulations.

M. Betancourt, Marcos R Betancourt, 2005, The Journal of chemical physics.

Pairwise energies for polypeptide coarse-grained models derived from atomic force fields.

M. Betancourt, S. J. Omovie, 2009, The Journal of chemical physics.

Empirical model of residue contact probabilities for polypeptides.

M. Betancourt, 2010, The Journal of chemical physics.