E input layer representing 35 features. 40 nodes in binary are used to represent the presence of 20 different residues at N and C terminus to the target peptide bond. Every node in the input layer has an independent coefficient to reveal its "relevance" to the network output. The hidden layer has 40 nodes and the activation function of the hidden layer is sigmoidal.<p><b>Copyright information:</b></p><p>Taken from "A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data"</p><p>http://www.biomedcentral.com/1471-2105/9/325</p><p>BMC Bioinformatics 2008;9():325-325.</p><p>Published online 30 Jul 2008</p><p>PMCID:PMC2529326.</p><p></p
