Add to ORKGElastic network models (ENMs) have over the last decade enjoyed considerable success in the study of macromolecular dynamics. These models have been used to predict the global dynamics of a variety of proteins and protein complexes
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...
Understanding the functions of biomolecules requires insight not only from structures but from dynam...
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...
AbstractBackgroundElastic network models (ENMs) are based on the simple idea that a protein can be d...
Background: Elastic network models (ENMs) are based on the simple idea that a protein can be describ...
This dissertation addresses the applications of Elastic Network Model (ENM) and Finite Element Analy...
ABSTRACT: Understanding the functions of biomolecules requires insight not only from structures but ...
<div><p>The elastic network model (ENM) is a widely used method to study native protein dynamics by ...
Elastic networks have been used as simple models of proteins to study their slow structural dynamics...
The role of ribonucleic acid (RNA) in molecular biology is shifting from a mere messenger between DN...
AbstractCoarse-grained (CG) models of large biomolecular complexes enable simulations of these syste...
International audienceCoarse-grained normal mode analyses of protein dynamics rely on the idea that ...
International audienceCoarse-grained normal mode analyses of protein dynamics rely on the idea that ...
Understanding the molecular flexibility and dynamics is central to the analysis of biomolecular func...
Background: Elastic network models (ENMs) are based on the simple idea that a protein can be describ...
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...
Understanding the functions of biomolecules requires insight not only from structures but from dynam...
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...
AbstractBackgroundElastic network models (ENMs) are based on the simple idea that a protein can be d...
Background: Elastic network models (ENMs) are based on the simple idea that a protein can be describ...
This dissertation addresses the applications of Elastic Network Model (ENM) and Finite Element Analy...
ABSTRACT: Understanding the functions of biomolecules requires insight not only from structures but ...
<div><p>The elastic network model (ENM) is a widely used method to study native protein dynamics by ...
Elastic networks have been used as simple models of proteins to study their slow structural dynamics...
The role of ribonucleic acid (RNA) in molecular biology is shifting from a mere messenger between DN...
AbstractCoarse-grained (CG) models of large biomolecular complexes enable simulations of these syste...
International audienceCoarse-grained normal mode analyses of protein dynamics rely on the idea that ...
International audienceCoarse-grained normal mode analyses of protein dynamics rely on the idea that ...
Understanding the molecular flexibility and dynamics is central to the analysis of biomolecular func...
Background: Elastic network models (ENMs) are based on the simple idea that a protein can be describ...
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...
Understanding the functions of biomolecules requires insight not only from structures but from dynam...
The Gaussian network model (GNM) can be used as a first approximation for describing the fluctuation...