ATP-Binding Site as a Further Application of Neural Networks to Residue Level Prediction
Document Type
Conference Proceeding
Publication Date
11-24-2008
Description
Similar neural network models based on single sequence and evolutionary profiles of residues have been successfully used in the past for predicting secondary structure, solvent accessibility, protein-, DNA- and carbohydrate- binding sites. ATP is a ubiquitous ligand in all living-systems, involved in most biological functions requiring energy and charge transfer. Prediction of ATP-binding site from single sequences and their evolutionary profiles at a high throughput rate can be used at genomic level as well as quick clues for site-directed mutagenesis experiments. We have developed a method for such predictions to demonstrate yet another application of sequence-base prediction algorithms using neural networks. This method can achieve 81% sensitivity and 69% specificity which are mutually adjustable in a wide range on a three-fold cross-validation data set.
Citation Information
Ahmad, Shandar; and Ahmad, Zulfiqar. 2008. ATP-Binding Site as a Further Application of Neural Networks to Residue Level Prediction. Proceedings of the International Joint Conference on Neural Networks. 2430-2434. https://doi.org/10.1109/IJCNN.2008.4634136 ISBN: 9781424418213