General Prediction
Predicts the subcellular location of eukaryotic proteins (use results of ChloroP and SignalP). Secretory signal peptides, mitochondrial targeting peptides and chloroplast transit peptides in eukaryotes.
http://www.cbs.dtu.dk/services/TargetP/
Protein Subcellular Localization Prediction (plant, animal,fungi)
http://wolfpsort.org/
bacterial protein subcellular localization prediction
http://www.psort.org/psortb/
The SecretomeP 2.0 server produces ab initio predictions of non-classical i.e. not signal peptide triggered protein secretion. The method queries a large number of other feature prediction servers to obtain information on various post-translational and localizational aspects of the protein, which are integrated into the final secretion prediction.
http://www.cbs.dtu.dk/services/SecretomeP/
LOCtree is a novel system of support vector machines (SVMs) that predict the subcellular localization of proteins, and DNA-binding propensity for nuclear proteins, by incorporating a hierarchical ontology of localization classes modeled onto biological processing pathways.
http://cubic.bioc.columbia.edu/services/loctree/
Twin-arginine translocation signal peptides in bacteria.
http://www.cbs.dtu.dk/services/TatP/
BaCelLo is a predictor for the subcellular localization of proteins in eukaryotes. It is based on a decision tree of several support vector machines (SVMs), it classifies up to four localizations for Fungi and Metazoan proteins and five localizations for Plant ones
http://gpcr.biocomp.unibo.it/bacello/
Subcellular Localisation Predictor (locations in plants and in other eukaryotes (TargetP data))..
http://pprowler.imb.uq.edu.au/
Subcellular localization predictor; CELLO is a multi-class SVM classification system.
http://cello.life.nctu.edu.tw/
The Proteome Analyst Specialized Subcellular Localization Server (PA-SUB) is part of Proteome Analyst (PA). PA is a web server built to predict protein properties, such as general function, in a high-throughput fashion. PA-SUB is specialized to predict the subcellular localization of proteins using established machine learning techniques.
http://www.cs.ualberta.ca/~bioinfo/PA/Sub/
Subcellular location in plants, other eukaryotes, fungi.
http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc/
PSLpred is a SVM based method to predict 5 major subcelullar localization (cytoplam, inner-membrane, outermembrane, extracellular, and periplasm) of Gram-negative bacteria.
http://www.imtech.res.in/raghava/pslpred/
pTARGET is a computational method to predict the subcellular localization of only eukaryotic proteins from animal species that include fungi and metazoans. Predictions are carried out based on the occurrence patterns of protein functional domains and the amino acid compositional differences in proteins from different subcellular locations. This method can predict proteins targeted to nine distinct subcellular locations that include cytoplasm, endoplasmic reticulum, extracellular/secreted, Golgi, lysosomes, mitochondria, nucleus, peroxysomes and plasma membrane.
http://bioapps.rit.albany.edu/pTARGET//
Protein subcellular LOCalization based on SVM and PSI-blast v.1.3
http://bioinformatics.ustc.edu.cn/locsvmpsi/locsvmpsi.php
Signal Peptides
SignalP 3.0 server predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms: Gram-positive prokaryotes, Gram-negative prokaryotes, and eukaryotes. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks and hidden Markov models.
http://www.cbs.dtu.dk/services/SignalP/
Mitochondrial & ER Localization
MITOPROT: Prediction of mitochondrial targeting sequences
http://ihg.gsf.de/ihg/mitoprot.html
Prediction of N-terminal sequence for mitochondrial, plastid and ER targeting sequences
http://urgi.versailles.inra.fr/predotar/predotar.html
Choroplast localization
Prediction of chloroplast transit peptides
http://www.cbs.dtu.dk/services/ChloroP/
Golgi Localization
Prediction of Golgi Type II membrane proteins based on their transmembrane domains.
http://ccb.imb.uq.edu.au/golgi/golgi_predictor.shtml
Lipoprotein signal peptides
Prediction of lipoproteins and signal peptides in Gram negative bacteria
http://www.cbs.dtu.dk/services/LipoP/
Peroxisomal Targeting Signal
Prediction of peroxisomal signal
http://mendel.imp.ac.at/mendeljsp/sat/pts1/PTS1predictor.jsp
Predicts peroxisomal proteins and Pfam domains
http://www.bioinfo.se/PeroxiP/
Nuclear Localization
PredictNLS is an automated tool for the analysis and determination of Nuclear Localization Signals (NLS).
http://cubic.bioc.columbia.edu/predictNLS/
Predicting Nuclear Localization of Proteins
http://www.sbc.su.se/~maccallr/nucpred/
NetNES 1.1 server predicts leucine-rich nuclear export signals (NES) in eukaryotic proteins using a combination of neural networks and hidden Markov models.
http://www.cbs.dtu.dk/services/NetNES-1.1/index.php
GPI-Anchor prediction
GPI lipid anchor predictor in animals
http://mendel.imp.ac.at/sat/gpi/gpi_server.html
Identification of GPI-anchor signals by a Kohonen Self Organizing Map
http://gpi.unibe.ch/