Prediction of protein coarse contact maps. Export

@article{Vullo03, abstract = {Prediction of topological representations of proteins that are geometrically invariants can contribute towards the solution of fundamental open problems in structural genomics like folding. In this paper we focus on coarse grained protein contact maps, a representation that describes the spatial neighborhood relation between secondary structure elements such as helices, beta sheets, and random coils. Our methodology is based on searching the graph space. The search algorithm is guided by an adaptive evaluation function computed by a specialized noncausal recursive connectionist architecture. The neural network is trained using candidate graphs generated during examples of successful searches. Our results demonstrate the viability of the approach for predicting coarse contact maps.}, author = {Vullo, Alessandro and Frasconi, Paolo}, citeulike-article-id = {5847079}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/15290778}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=15290778}, issn = {0219-7200}, journal = {Journal of bioinformatics and computational biology}, keywords = {predictions, protein\_structure, proteins}, month = {July}, number = {2}, pages = {411--431}, posted-at = {2009-09-28 14:58:11}, priority = {4}, title = {Prediction of protein coarse contact maps.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/15290778}, volume = {1}, year = {2003} }

TY - JOUR ID - Vullo03 L3 - citeulike-article-id:5847079 N2 - Prediction of topological representations of proteins that are geometrically invariants can contribute towards the solution of fundamental open problems in structural genomics like folding. In this paper we focus on coarse grained protein contact maps, a representation that describes the spatial neighborhood relation between secondary structure elements such as helices, beta sheets, and random coils. Our methodology is based on searching the graph space. The search algorithm is guided by an adaptive evaluation function computed by a specialized noncausal recursive connectionist architecture. The neural network is trained using candidate graphs generated during examples of successful searches. Our results demonstrate the viability of the approach for predicting coarse contact maps. IS - 2 JF - Journal of bioinformatics and computational biology SN - 0219-7200 EP - 431 TI - Prediction of protein coarse contact maps. VL - 1 SP - 411 KW - predictions KW - protein_structure KW - proteins AU - Vullo, Alessandro AU - Frasconi, Paolo PY - 2003/07// UR - http://view.ncbi.nlm.nih.gov/pubmed/15290778 ER -