Improving Protein Structure Prediction by New Strategies: Experimental Insights and the Genetic Algorithm $

关键词: Fold prediction 、 Bioinformatics 、 Computer science 、 Crowding in 、 Selection (genetic algorithm) 、 Experimental data 、 Genetic algorithm 、 Domain (software engineering) 、 Protein structure prediction 、 Fitness function 、 Algorithm

摘要: Three different approaches to improve tertiary fold prediction using the genetic algorithm are discussed: (i) Refinement of search strategy, (ii) combination and experiment (iii) inclusion experimental data as selection criteria into algorithm. Examples from our current work presented for refined strategies against crowding in solution space, definition domain boundaries secondary structure with experiment, direct incorporation experimentally known distance constraints fitness function.