eSLDB is a database of protein subcellular localization annotation for eukaryotic organisms. It contains experimental annotations derived from primary protein databases, homology based annotations and computational predictions.
DBSubLoc is a database of protein subcellular localization. This database contains proteins from primary protein database SWISS-PROT and PIR.
A database of organelle proteins, and subcellular structures / complexes
LOCATE is a curated database that houses data describing the membrane organization and subcellular localization of proteins from the RIKEN FANTOM4 mouse and human protein sequence set.
LocDB is a expert curated database that collects experimental annotations for the subcellular localization of proteins in Human (Homo sapiens) and Weed (Arabidopsis thaliana).
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.
bacterial protein subcellular localization prediction
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.
Events News Research CBS CBS Publications Bioinformatics Staff Contact About Internal CBS CBS Other CBS >> CBS Prediction Servers >> TatP TatP 1.0 Server TatP 1.0 server predicts the presence and location of Twin-arginine signal peptide cleavage sites in bacteria. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of two artificial neural networks.
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
Subcellular Localisation Predictor (locations in plants and in other eukaryotes (TargetP data))..
Subcellular localization predictor; CELLO is a multi-class SVM classification system.
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.
Subcellular location in plants, other eukaryotes, fungi.
PSLpred is a SVM based method to predict 5 major subcelullar localization (cytoplam, inner-membrane, outermembrane, extracellular, and periplasm) of Gram-negative bacteria.
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.
Database of Protein Subcellular Localization
ProTeus (PROtein TErminUS) is a tool for identification of short linear signatures in protein termini. It is based on a positional-based search method for revealing short significant signatures in termini of proteins.
SignalP 4.1 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.
PrediSi (PREDIction of SIgnal peptides) is a software tool for predicting signal peptide sequences and their cleavage positions in bacterial and eukaryotic proteins.
Signal-3L is an automated method for predicting signal peptide sequences and their cleavage sites in eukaryotic and bacterial protein sequences that uses a 3-layer approach for predicting signal peptides.
Online tool to find and list homologies of published signal sequences with the input DNA sequence.
450 Signal Sequences of E. coli Cell Envelope Proteins compilated by ECCE (The E. coli Cell Envelope Protein Data Collection)
iPSORT is a subcellular localization site predictor for N-terminal sorting signals. Given a protein sequence , it will predict whether it contains a Signal Peptide (SP), Mitochondrial Targeting Peptide (mTP), or Chloroplast Transit Peptide (cTP).
Prediction of Signal Peptides in Archaea with Hidden Markov Models.
Prediction of Lipoprotein and Secretory Signal Peptides in Gram-positive Bacteria with Hidden Markov Models.
High performance system for signal peptide prediction.
MITOPROT: Prediction of mitochondrial targeting sequences
Prediction of N-terminal sequence for mitochondrial, plastid and ER targeting sequences
Prediction of chloroplast transit peptides
Prediction of Golgi Type II membrane proteins based on their transmembrane domains.
Prediction of lipoproteins and signal peptides in Gram negative bacteria.
Prediction of Lipoprotein and Secretory Signal Peptides in Gram-positive Bacteria with Hidden Markov Models.
Predicting Nuclear Localization of Proteins
NetNES 1.1 server predicts leucine-rich nuclear export signals (NES) in eukaryotic proteins using a combination of neural networks and hidden Markov models.
GPI lipid anchor predictor in animals
Identification of GPI-anchor signals by a Kohonen Self Organizing Map
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