We present an approach to learning and using probabilistic graphical models of residue coupling. These models capture significant conservation and coupling ...

Mar 1, 2005 · We present the first algorithm to infer an undirected graphical model underlying residue coupling in protein families. We bring in ideas from ...

Abstract—Many statistical measures and algorithmic tech- niques have been proposed for studying residue coupling in protein families.

We present the first algorithm to infer an undirected graphical model representing residue coupling in protein families. Such a model, which we call a residue ...

ABSTRACT. Identifying residue coupling relationships within a protein family can provide important insights into the family's evo-.

Mar 1, 2005 · We present the first algorithm to infer an undirected graphical model representing residue coupling in protein families. Such a model serves as ...

Jun 12, 2021 · We briefly review graphical models, in particular Restricted Boltzmann Machines, an unsupervised learning framework that encompasses DCA by ...

Nov 21, 2008 · This paper develops an approach for designing protein variants by sampling sequences that satisfy residue constraints encoded in an ...

Residue interaction networks (RINs) provide graph-based representations of interaction networks within proteins, providing important insight into the ...

In this paper we apply the complex networks theory, widely used to analyze co-affiliation systems in the social and ecological contexts, to map groups of ...