Prédiction de localisation cellulaire


VersionMAJ

hmmtop

2.12004-09-25DownloadDoc
Prediction of transmembrane helices and topology for transmembrane proteins using hidden Markov models

Remarque
Run Unix # hmmtopRun Web #

VersionMAJ

memsat3

32010-12-28DownloadDoc
Transmembrane Protein Modelling

Remarque
Run Unix # memsat3 "query" "database" ou runmemsat.sh "query" "database"Run Web #

VersionMAJ

phobius

1.012010-03-23DownloadDoc
A combined transmembrane topology and signal peptide prediction method.

Remarque http://www.ncbi.nlm.nih.gov/pubmed/15111065?dopt=Abstract
Run Unix # phobius.pl [options] [infile]Run Web #

VersionMAJ

psort

3.0.32012-05-30DownloadDoc
PSORT is a computer program for the prediction of protein localization sites in cells. It receives the information of an amino acid sequence and its source orgin, e.g., Gram-negative bacteria, as inputs. Then, it analyzes the input sequence by applying the stored rules for various sequence features of known protein sorting signals. Finally, it reports the possiblity for the input protein to be localized at each candidate site with additional information.

Remarque
Run Unix # psortRun Web #

VersionMAJ

signalp

4.02014-05-07DownloadDoc
Détection de séquence signal et de site de clivage sur les séquences protéiques de bactéries Gram+, Gram- et d'eucaryotes.

Remarque The SIGNALP package is a property of Center for Biological Sequence Analysis It may be downloaded only by special agreement (contact software@cbs.dtu.dk).
Run Unix # signalpRun Web #

VersionMAJ

SurfG+

1.022012-07-13DownloadDoc
SurfG+ is a tool to predict the protein localization in frame-psoitive bacteria. Current protein localization protocols are not suited to this prediction task as they ignore the potential surface exposition of many membrane-associated proteins. Therefore, we developed a new flow scheme, for the processing of protein sequence data with the particular aim of identification of potentially surface exposed (PSE) proteins from Gram-positive bacteria.

Remarque See Barinov A, Loux V, Hammani A, Nicolas P, Langella P, Ehrlich D, et al. Prediction of surface exposed proteins in Streptococcus pyogenes, with a potential application to other Gram-positive bacteria. Proteomics. 2009 Jan.;9(1):61–73.  
Run Unix # SurfgRun Web #

VersionMAJ

tmhmm

2.0c 2007-11-22DownloadDoc
tmhmm is one of the better prediction methods of transmembrane helices in proteinss

Remarque tmhmm ma_sequence.fasta puis le resultat est genere sur la sortie standard (pas tres bavard) et dans un repertoire nomme TMHMM_ avec etant le PID du processus qui l a genere.
Run Unix # tmhmm Run Web # http://www.cbs.dtu.dk/services/TMHMM/

VersionMAJ

tmmod

2009-02-23DownloadDoc
An Improved Hidden Markov Model for Transmembrane Protein Topology Prediction and Its Applications to Complete Genomes

Remarque
Run Unix # tmmodRun Web #

VersionMAJ

WolfPsort

0.22007-04-02DownloadDoc
WoLF PSORT predicts the subcellular localization sites of proteins based on their amino acid sequences.

Remarque
Run Unix # runWolfPsortSummary Run Web #

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