Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Background: The ab initio protein folding problem consists of predicting protein tertiary structure from a given amino acid sequence by minimizing an energy function; it is one of...
We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classific...
Timothy Meekhof, Gary W. Daughdrill, Robert B. Hec...
Computational protein design can be formulated as an optimization problem, where the objective is to identify the sequence of amino acids that minimizes the energy of a given prot...
Noah Ollikainen, Ellen Sentovich, Carlos Coelho, A...
We present a new representation for a genetic algorithm to evolve molecular structures representing possible drugs that bind to a given protein target receptor. Our representation...