Genetic Algorithm for Ab Initio Protein Structure Prediction.

      Аннотация: Protein is a sequence of amino acids bounded into a linear chain that adopts a specific folded three-dimensional (3D) shape. This specific folded shape enables protein to perform specific tasks. Amongst various available computational methods, the protein structure prediction by the ab initio approach is promising and can help to unravel the relationship between sequence and its associated structure. This book is focused on the ab initio protein structure prediction (PSP), by developing novel Genetic Algorithm (GA) for an efficient and effective conformation search of low resolution models. The book also proposes a novel low resolution model, called hHPNX model providing more accurate predictions compared to the existing low resolution HP models. Extensions of these developed algorithms are very promising for high resolution models.

Ключевые слова: genetic algorithm, Heuristic Search, Lattice Model, Schema Theorem, Non-Isomorphic Encoding, Ab Initio Protein Structure Prediction