SLPred: A multi-view subcellular localization prediction tool

1. The tool consists of nine independently developed model for the proteins which have annotation with nine subcellular locations: Cytoplasm, Nucleus, Cell Membrane, Mitochondrion, Secreted, Endoplasmic reticulum, Golgi apparatus, Lysosome and Peroxisome.
2. SLPred exploits the features of forty different protein descriptors from the publicly available tools: POSSUM, iFeature and SPMAP.
3. Support Vector Machine (SVM) is used to construct probabilistic prediction models, which produces probabilistic scores indicating the localization probability for a query protein sequence.
4. A weighted score is calculated based on the obtained probabilistic scores from seven feature-based probabilistic prediction models (SVMs) by employing weighted mean voting.
5. Binary prediction is given by applying thresholding on the weighted score.