Fast optimization of statistical potentials for structurally constrained phylogenetic models.

ABSTRACT:

Background

Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC) models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms.

Results

Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to

SUBMITTER: Bonnard C 

PROVIDER: S-EPMC2754480 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature