PREDICTION OF PROTEIN SUPERSECONDARY STRUCTURE WITH ARTIFICIAL NEURO NETWORK METHOD
用人工神经网络方法预测蛋白质超二级结构

The artifical neuro network method is applied to pndict the proals supecondary structure(Motif), which is defined as the combination of secondary structural elements by short conned peptide. We find that the local anangelnent of amino aam fluency is of gutsignificance to the supereerendary structare. Therefore the motif structare can be pndied byits parry strUCtUre at a higher pndiction ratio (75%-80%) than the pndiction of secondarysthe. The backward propagation algorithm of aritifical neuro network is modal by using acoefficient ("momentum"), leading to an effat of faster convergence of weights matrix.