Figure 3From: Transmembrane helix prediction using amino acid property features and latent semantic analysisBlock diagram of TMpro prediction. Primary sequence of protein (amino acid sequence) is input to the system. (A) maps it to 5 amino acid property se-quences. The output has size 5 x L (rows x columns). These 5 sequences form input to (B) which performs windowed analysis, and outputs a matrix of counts of 10 properties (C1 to C10) for each window position. This output has the size 10xL-l+1. The outputs from (B) for all proteins are collected together and singular value decomposition is performed by C. During testing phase, an SVD approximation is performed for the matrix of a single test protein. The output of this block (C) forms the final features used by neural network. (D) Features are evaluated by the NN model and a 2-state prediction is output for each residue (TM, non-TM). An analog value also is output ranging from -1 to 1 that indicates the closeness of the feature to non-TM or to TM correspondingly.Back to article page