Improving protein secondary structure prediction using a multi-modal BP method
Computers in Biology and Medicine
| Hi-index | 0.00 |
Eight representative physicochemical properties of amino acids are considered to encode each residue and correlative information is examined in relation to the formation of protein secondary structure. Features salient at the coarse level are first gleaned through vector quantization technique and then more refined class-specific features are identified based on the vector element-wise analysis. Effectiveness of the method has been validated in experiments to predict secondary structure using the widely used protein sequence sets. Heuristic rationale for advantage of using physicochemical properties of amino acids over the conventional statistics-based method relying on the frequency of residue occurrence is also presented.