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Computer Resources for Proteome Annotation and Proteomics

The proteome is the entire complement of proteins expressed by an organism, tissue, cell or a genome. More specifically, it is the expressed proteins at a given time point under specific conditions. A cellular proteome is the set of proteins found in a particular cell type under a particular set of environmental conditions such as exposure to hormone. The proteome is not limited to the number of the sequences of the proteins present.

Thus it is evident that the proteome is larger than the genome, especially in eukaryotes. This is due to post-translational modifications like glycosylation or phosphorylation etc., and alternative splicing of genes in eukaryotes.

Understanding of the proteome requires knowledge of:
    • the structure of the proteins in the proteome and
    • the functional interaction between the proteins.
List of computer resources available in the field of proteome annotation and proteomics is given below:

Servers integrated at CRDD

ServerDescription
AC2DGel This is a web server for analysis and comparison of two-dimensional electrophoresis (2-DE) Gel images. It helps in annotating the virual 2-D gel image proteins on the basis of known molecular weight andpH scales of the markers.
ESLpred This is a SVM based method for predicting subcellular localization of Eukaryotic proteins using dipeptide composition and PSIBLAST generated pfofile Using this server user may know the function of their protein based on its location in cell. (Bhasin, M. and Raghava, G. P. S., (2004) Nucleic Acid Res. 32(Web Server issue):W414-9).
NRpred This is a SVM based tool for the classification of nuclear receptors on the basis of amino acid composition or dipeptide composition. The overall prediction accuracy of amino acid composition and dipeptide composition based methods is 82.6% and 97.2% (Bhasin, M. and Raghava, G. P. S., (2004) Journal of Biological Chemistry 279(22):23262-6
GPCRpred This is a server forpredicting G-protein-coupled receptors and for classifying them in families and sub-families. This server can play vital role in drug design, as GPCR are commonly used as drug targets (Bhasin, M. and Raghava, G. P. S., (2004) Nucleic Acid Res. 32(Web Server issue):W383-9)
GPCRSclass This is a dipeptide composition based method for predicting Amine Type of G-protein-coupled receptors. In this method type amine is predicted from dipeptide composition of proteins using SVM. (Bhasin M, Raghava GP. (2005) 33(Web Server issue):W143-7)
Comp2DGelComparison, management and access of 2D gel electrophoresis.
DNASIZE This web-server allow to compute the length of DNA or protein fragments from its electropheric mobility using a graphical method (Raghava, G. P. S. (2001) Biotech Software and Internet Report, 2:198).
HSLpred This server allows predicting the subcellulare localization of human proteins. This is based on various type of residue composition of proteins using SVM technique. (Garg A, Bhasin M, Raghava GP. J Biol Chem. (2005) 280(15):14427-32)
PSLpredA method for subcellular localization proteins belongs to prokaryotic genomes. The pathogen play an important role in our life. (Bhasin M, Garg A, Raghava GP. Bioinformatics. (2005) 21(10):2522-4)
MANGOPrediction of manually annotated proteins in Genome Ontology (GO). This server is based on nearest  neighbor  method   (NNM).
BtxpredThe aim of BTXpred server is to predict bacterial toxins and its function from primary amino acid sequence.
MitpredThis server predicts mitochondril proteins
SRTpredThis server classifies protein sequence as secretory or non-secretory proteins.
HemopredIt allows users to predict hemoglobin protein.
VGIchanThe aim of this server is to predict voltage gated ion-channels and classify them into sodium, potassium, calcium and chloride ion channels from primary amino sequences.
SGpredThis server allows user to identify and visulaze the genes which have different expression level in normal and disease conditions.
LGEpredThis server allows user to analsis the expresion data (Microarray Data) where it calculate correlation coefficient between amino acid residue and gene expression level.
NTXpredThe aim of this server is to predict neurotoxins and it source and probable functions from primary amino acid sequences.
VICMpredThis server aids in broad functional classification of bacterial proteins into virulence factors, information molecule, cellular process and metabolism molecule.(Saha, S. and Raghava, G. P. S.(2006) Genomics Proteomics & Bioinformatics(In Press) )
AlgPredThis server predicts allergens from amino acid sequences using presence of IgE epitopes, MEME/MAST motif, allergen representative peptides BLAST search and SVM based method(Saha, S. and Raghava, G. P. S.(2006) Nucleic Acids Research(In Press) )
RBPredThis server predicts rice leaf blast severity(%) based on the weather parameters and utilizes the regression mode of SVM.
RSL-PredThis server predicts subcellular localization of rice proteins e.g, chloroplast, cytoplasmic, mitochondrial and nuclear proteins.
AntiBPThis is a QM, SVM, ANN based server that predicts whether a peptides sequences is an antibacterial peptide or not. It also identifies antibacterial peptides in a protein sequence.
COPidThis server find proteins that are amino acid compositionaly similar to other proteins present in database. It can be used to compare and calculate amino acid/dipeptide composition, and can form distance matrix for phylogenetic analysis. It can also be used for patterns generation for SNNS, SVM and Timble..
siRNAPredThis server predicts siRNA and utilize SVM based on composition.


Web Servers/Databases/Mirror Sites


Web Servers

1. Subcellular Location Prediction Servers

S. No. Name Description Link Standalone Available
1 NetNES Leucine-rich nuclear exhttp://www.cbs.dtu.dk/services/NetNESport signals (NES) in eukaryotic proteins http://www.cbs.dtu.dk/services/NetNES/ Yes
2 PSORT Prediction of protein subcellular localization http://www.psort.org/ Yes
3 SecretomeP Non-classical and leaderless secretion of proteins http://www.cbs.dtu.dk/services/SecretomeP/ Yes
4 TargetP Prediction of subcellular location http://www.cbs.dtu.dk/services/TargetP/ Yes
5 TatP Twin-arginine signal peptides http://www.cbs.dtu.dk/services/TatP/ No
6 DAS Prediction of transmembrane regions in prokaryotes using the Dense Alignment Surface method http://www.sbc.su.se/~miklos/DAS/ No
7 HMMTOP Prediction of transmembrane helices and topology of proteins http://www.enzim.hu/hmmtop/ Yes
8 PredictProtein Prediction of transmembrane helix location and topology http://www.predictprotein.org/ No
9 TMAP Transmembrane detection based on multiple sequence alignment http://bioinfo4.limbo.ifm.liu.se/tmap/index.html No
10 SOSUI Prediction of transmembrane regions http://bp.nuap.nagoya-u.ac.jp/sosui/ No
11 TMHMM Prediction of transmembrane helices in proteins http://www.cbs.dtu.dk/services/TMHMM-2.0/ Yes
12 TMpred Prediction of transmembrane regions and protein orientation http://www.ch.embnet.org/software/TMPRED_form.html No
13 TopPred Topology prediction of membrane proteins http://mobyle.pasteur.fr/cgi-bin/MobylePortal/portal.py?form=toppred No
14 PSLDoc uses document classification techniques and incorporates a probabilistic latent semantic analysis with a support vector machine model, for prediction on prokaryotes and eukaryotes. http://bio-cluster.iis.sinica.edu.tw/~bioapp/PSLDoc2/index.php No
16 PSL101 hybrid prediction method for Gram-negative bacteria that combines a one-versus-one support vector machine(SVM) model and a structure homology approach http://bio-cluster.iis.sinica.edu.tw/~bioapp/PSL101/ No
17 SLP-Local predicts localizations for chloroplast, mitochondria, secretory pathway, and other locations (nucleus or cytosol) for eukaryotic proteins, as well as cytoplasm, extracell, and periplasm for Gram negative organisms. http://sunflower.kuicr.kyoto-u.ac.jp/~smatsuda/slplocal.html No
18 CELLO uses a two-level Support Vector Machine system to assign localizations to both prokaryotic and eukaryotic proteins. http://cello.life.nctu.edu.tw/ No
20 PA-SUB This specialized server available at the PENCE Proteome Analyst site is able to classify Gram-negative, Gram-positive, fungi, plant and animal proteins to many localization sites. http://www.cs.ualberta.ca/%7Ebioinfo/PA/Sub/index.html No
21 LOCtree LOCtree is a eukaryotic and prokaryotic localization prediction tool http://cubic.bioc.columbia.edu/cgi-bin/var/nair/loctree/querytd> No
22 SubLoc uses Support Vector Machine to assign a prokaryotic protein to the cytoplasmic, periplasmic, or extracellular sites, and a eukaryotic protein to the cytoplasmic, mitochondrial, nuclear, or extracellular sites. http://www.bioinfo.tsinghua.edu.cn/SubLoc/ No
23 EpiLoc a text-based system for predicting animal, plant and fungal protein subcellular locations. http://epiloc.cs.queensu.ca/ No
24 ProLoc-GO utilizes Gene Ontology terms for sequenced-based prediction of subcellular localization. http://iclab.life.nctu.edu.tw/prolocgo/index.php No
25 AAIndexLoc predicts protein subcellular localization by using amino acid composition and physicochemical properties. http://aaindexloc.bii.a-star.edu.sg/ No
26 SCLFA predicts localizations by feature vectors based on amino acid composition (frequency) and sequence alignment. Subcellular locations predicted include chloroplast, mitochondria, secretory pathway, and other locations (nucleus or cytosol) for eukaryotic proteins http://sunflower.kuicr.kyoto-u.ac.jp/~tamura/slpfa.html No
27 SherLoc intergrates several sequence and text-based features and provides predictions for plant, animal, and fungal proteins. http://www-bs.informatik.uni-tuebingen.de/Services/SherLoc/ No
28 SLPS Subcellular Localization Predicting System, predicts localization using a Nearest Neighbor Algorithm (NNA) and incorporating a protein functional domain profile. http://pcal.biosino.org/sub_loc.html No
29 BaCelLo predictor for five classes of eukaryotic subcellular localization (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) and it is based on different SVMs organized in a decision tree. http://gpcr.biocomp.unibo.it/bacello/ No
30 Protein Prowler a multi-layer classifer system for predicting the subcellular localization of proteins based on their amino acid sequence. It classifies eukaryotic targeting signals as secretory, mitochondrion, chloroplast or other. http://pprowler.imb.uq.edu.au/ No
31 pTARGET uses amino acid composition and localization-specific Pfam domains to assign a eukaryotic protein to one of nine localization sites. http://bioapps.rit.albany.edu/pTARGET/ No
32 Golgi predictor predicts Golgi Type II membrane proteins and can discriminate between proteins destined for the Golgi apparatus or other post-Golgi locations. http://ccb.imb.uq.edu.au/golgi/golgi_predictor.shtml No
34 LOCSVMPSI a eukaryotic localization prediction method that incorporates evolutionary information into its predictions. The method uses PSI-BLAST and support vector machine to generate predictions for up to 12 localization sites. http://bioinformatics.ustc.edu.cn/locsvmpsi/locsvmpsi.php No
35 PSLT a Bayesian network-based method that predicts human protein localization based on motif/domain co-occurence. http://www.mcb.mcgill.ca/%7Ehera/PSLT/ No
36 ESLPred uses Support Vector Machine and PSI-BLAST to assign eukaryotic proteins to the nucleus, mitochondrion, cytoplasm, or extracellular space. http://www.imtech.res.in/raghava/eslpred/ No
37 Nuc-PLoc a web-server for predicting protein subnuclear localization by fusing PseAA composition and PsePSSM. http://chou.med.harvard.edu/bioinf/Nuc-PLoc/ No
38 NUCLEO predicts possible nuclear localization by taking into consideration of dually localized proteins. It uses an SVM-based approach with a custom kernel that employs a composite spectrum (or multiple k-mer) encoding conjoined with a bit vector indicating the presence or absence of a range of sequence motifs known to be important for nuclear proteins. http://pprowler.itee.uq.edu.au/Nucleo-Release-1.0/ No
39 NucPred predicts possible nuclear localization by using a genetic programming-based algorithm. http://www.sbc.su.se/~maccallr/nucpred/ No
40 ProLoc predicts subnuclear localizations using an evolutionary SVM based classifier with automatic selection from a large set of physicochemical composition (PCC) features. http://iclab.life.nctu.edu.tw/proloc/ No
41 Subnuclear Compartments Prediction System predicts subnuclear localization by combining an SVM-based system for sequence analysis with a nearest-neighbor classifier using a similarity measure derived from the GO annotation terms for the protein sequences. http://array.bioengr.uic.edu/subnuclear.htm No
42 NetNES predicts nuclear export signals using neural network and HMMs. http://www.cbs.dtu.dk/services/NetNES/ No
43 PredictNLS uses nuclear localization signal motifs to predict whether a protein might be localized to the nucleus. http://cubic.bioc.columbia.edu/predictNLS/ Yes
44 ChloroP Prediction of chloroplast transit peptides http://www.cbs.dtu.dk/services/ChloroP/ Yes
45 LipoP Prediction of lipoproteins and signal peptides in Gram negative bacteria http://www.cbs.dtu.dk/services/LipoP/ yes
46 MITOPROT Prediction of mitochondrial targeting sequences http://ihg2.helmholtz-muenchen.de/ihg/mitoprot.html Yes
47 PATS Prediction of apicoplast targeted sequences http://gecco.org.chemie.uni-frankfurt.de/pats/pats-index.php No
48 PlasMit Prediction of mitochondrial transit peptides in Plasmodium falciparum http://gecco.org.chemie.uni-frankfurt.de/plasmit/index.html No
49 Predotar Prediction of mitochondrial and plastid targeting sequences http://urgi.versailles.inra.fr/predotar/predotar.html No
50 PTS1 Prediction of peroxisomal targeting signal 1 containing proteins http://mendel.imp.ac.at/mendeljsp/sat/pts1/PTS1predictor.jsp No
51 SignalP Prediction of signal peptide cleavage sites http://www.cbs.dtu.dk/services/SignalP/ Yes

2. Servers Calculating Physiochemical Properties of amino acids

S. No Name Description Link Standalone Available
1 AACompIdent Identify a protein by its amino acid composition http://expasy.org/tools/aacomp/ No
2 AACompSim Compare the amino acid composition of a UniProtKB/Swiss-Prot entry with all other entries http://expasy.org/tools/aacsim/ No
3 TagIdent Identify proteins with isoelectric point (pI), molecular weight (Mw) and sequence tag, or generate a list of proteins close to a given pI and Mw http://expasy.org/tools/tagident.html No
4 MultiIdent Identify proteins with isoelectric point (pI), molecular weight (Mw), amino acid composition, sequence tag and peptide mass fingerprinting data http://expasy.org/tools/multiident/ No
5 ProtParam Physico-chemical parameters of a protein sequence (amino-acid and atomic compositions, isoelectric point, extinction coefficient, etc.) http://expasy.org/tools/protparam.html No
6 Compute pI/Mw Compute the theoretical isoelectric point (pI) and molecular weight (Mw) from a UniProt Knowledgebase entry or for a user sequence http://expasy.org/tools/pi_tool.html No
7 IsotopIdent Predicts the theoretical isotopic distribution of a peptide, protein, polynucleotide or chemical compound http://education.expasy.org/student_projects/isotopident/htdocs/ No
8 Aldente Identify proteins with peptide mass fingerprinting data. A new, fast and powerful tool that takes advantage of Hough transformation for spectra recalibration and outlier exclusion http://www.expasy.org/tools/aldente/ No
9 Mascot Peptide mass fingerprint from Matrix Science Ltd., London http://www.matrixscience.com/search_form_select.html No
10 PepMAPPER Peptide mass fingerprinting tool from UMIST, UK http://www.nwsr.manchester.ac.uk/mapper/ No
11 ProteinProspector UCSF tools for peptide masses data (MS-Fit, MS-Pattern, MS-Digest, etc.) http://prospector.ucsf.edu/ No
12 ProFound Search known protein sequences with peptide mass information from Rockefeller and NY Universities http://prowl.rockefeller.edu/prowl-cgi/profound.exe No
13 Phenyx Protein and peptide identification/characterization from MS/MS data from GeneBio, Switzerland http://phenyx.vital-it.ch/pwi/login/login.jsp No
14 OMSSA MS/MS peptide spectra identification by searching libraries of known protein sequences http://pubchem.ncbi.nlm.nih.gov/omssa/ No
15 PepFrag Search known protein sequences with peptide fragment mass information from Rockefeller and NY Universities http://prowl.rockefeller.edu/prowl/pepfrag.html No
16 MALDIPepQuant Quantify MALDI peptides (SILAC) from Phenyx output http://expasy.org/tools/maldipepquant/ No
17 pIcarver Visualize theoretical distributions of peptide pI on a given pH range and generate fractions with similar peptide frequencies http://expasy.org/tools/picarver/ No
18 GlycanMass calculate the mass of an oligosaccharide structure http://expasy.org/tools/glycomod/glycanmass.html No
19 GlycoMod Predict possible oligosaccharide structures that occur on proteins from their experimentally determined masses (can be used for free or derivatized oligosaccharides and for glycopeptides) http://expasy.org/tools/glycomod/ No

3. Servers Predicting Post-translational Modifications

S. No Name Description Links Standalone Available
1 PeptideMass Calculate masses of peptides and their post-translational modifications for a UniProtKB/Swiss-Prot or UniProtKB/TrEMBL entry or for a user sequence http://expasy.org/tools/peptide-mass.html No
2 FindMod Predict potential protein post-translational modifications and potential single amino acid substitutions in peptides. Experimentally measured peptide masses are compared with the theoretical peptides calculated from a specified Swiss-Prot entry or from a user-entered sequence, and mass differences are used to better characterize the protein of interest http://expasy.org/tools/findmod/ No
3 FindPept Identify peptides that result from unspecific cleavage of proteins from their experimental masses, taking into account artefactual chemical modifications, post-translational modifications (PTM) and protease autolytic cleavage http://expasy.org/tools/findpept.html No
4 Popitam identification and characterization tool for peptides with unexpected modifications (e.g. post-translational modifications or mutations) by tandem mass spectrometry http://expasy.org/tools/popitam/ No
5 DictyOGlyc Prediction of GlcNAc O-glycosylation sites in Dictyostelium http://www.cbs.dtu.dk/services/DictyOGlyc/ No
6 NetCGlyc C-mannosylation sites in mammalian proteins http://www.cbs.dtu.dk/services/NetCGlyc/ Yes
7 NetOGlyc Prediction of O-GalNAc (mucin type) glycosylation sites in mammalian proteins http://www.cbs.dtu.dk/services/NetOGlyc/ Yes
8 NetGlycate Glycation of epsilon amino groups of lysines in mammalian proteins http://www.cbs.dtu.dk/services/NetGlycate/ Yes
9 NetNGlyc Prediction of N-glycosylation sites in human proteins http://www.cbs.dtu.dk/services/NetNGlyc/ Yes
10 OGPET Prediction of O-GalNAc (mucin-type) glycosylation sites in eukaryotic (non-protozoan) proteins http://ogpet.utep.edu/OGPET/index.php Yes
11 YinOYang O-beta-GlcNAc attachment sites in eukaryotic protein sequences http://www.cbs.dtu.dk/services/YinOYang/ Yes
12 big-PI Predictor GPI Modification Site Prediction http://mendel.imp.ac.at/sat/gpi/gpi_server.html No
13 GPI-SOM Identification of GPI-anchor signals by a Kohonen Self Organizing Map http://gpi.unibe.ch/ Yes
14 Myristoylator Prediction of N-terminal myristoylation by neural networks http://expasy.org/tools/myristoylator/ No
15 NMT Prediction of N-terminal N-myristoylation http://mendel.imp.ac.at/myristate/SUPLpredictor.htm No
16 CSS-Palm Palmitoylation site prediction with CSS http://bioinformatics.lcd-ustc.org/css_palm/index.php Yes
17 PrePS Prenylation Prediction Suite http://mendel.imp.ac.at/sat/PrePS/index.html No
18 NetAcet Prediction of N-acetyltransferase A (NatA) substrates (in yeast and mammalian proteins) http://www.cbs.dtu.dk/services/NetAcet/ Yes
19 NetPhos Prediction of Ser, Thr and Tyr phosphorylation sites in eukaryotic proteins http://www.cbs.dtu.dk/services/NetPhos/ Yes
20 NetPhosK Kinase specific phosphorylation sites in eukaryotic proteins http://www.cbs.dtu.dk/services/NetPhosK/ No
21 NetPhosYeast Serine and threonine phosphorylation sites in yeast proteins http://www.cbs.dtu.dk/services/NetPhosYeast/ No
22 Sulfinator Prediction of tyrosine sulfation sites http://expasy.org/tools/sulfinator/ No
23 SulfoSite Prediction of tyrosine sulfation sites http://sulfosite.mbc.nctu.edu.tw/ No
24 SUMOplot Prediction of SUMO protein attachment sites http://www.abgent.com/doc/sumoplot No
25 TermiNator Prediction of N-terminal modification http://www.isv.cnrs-gif.fr/terminator3/index.html No
26 NetPicoRNA Prediction of protease cleavage sites in picornaviral proteins http://www.cbs.dtu.dk/services/NetPicoRNA/ No
27 NetCorona Coronavirus 3C-like proteinase cleavage sites in proteins http://www.cbs.dtu.dk/services/NetCorona/ No
28 ProP Arginine and lysine propeptide cleavage sites in eukaryotic protein sequences http://www.cbs.dtu.dk/services/ProP/ Yes
29 PeptideCutter Predicts potential protease and cleavage sites and sites cleaved by chemicals in a given protein sequence http://expasy.org/tools/peptidecutter/ No

Databases

1. Proteomics (2D and MALDI) Databases

S. No Name Description Link Standalone Available
1 SWISS-2DPAGE contains data on proteins identified on various 2-D PAGE and SDS-PAGE reference maps. http://www.expasy.org/swiss-2dpage No
2 WORLD-2DPAGE A Dynamic Portal to query simultaneously World-Wide Gel-based Proteomics Databases http://www.expasy.org/world-2dpage No
3 DOSAC-COBS 2D-PAGE 2D-PAGE server to query 'DOSAC-COBS 2D Page http://www.dosac.unipa.it/cgi-bin/2d/2d.cgi No
4 Plasmo2Dbase Plasmodium falciparum 2-DE database at Indian Institute of Science, Bangalore, India http://utlab3.biochem.iisc.ernet.in/cgi-bin/Plasmo2Dbase/Plasmo2Dbase.cgi No
5 Cornea-2DPAGE Human cornea, Department of Molecular Biology, Faculty of Science, Aarhus University, Denmark http://www.cornea-proteomics.com/ No
6 REPRODUCTION-2DPAGE 2D-PAGE database (Human ovary, Mouse testis) http://reprod.njmu.edu.cn/cgi-bin/2d/2d.cgi No
7 ANU-2DPAGE 2-DE database (Rice anther and Medicago truncatula) of the Australian National University, Canberra, Australia http://semele.anu.edu.au/2d/2d.html No
8 OGP-WWW Oxford GlycoProteomics database (Human platelet) http://proteomewww.glycob.ox.ac.uk/2d/2d.html No
9 PHCI-2DPAGE Parasite host cell interaction 2D-PAGE database http://www.gram.au.dk/2d/2d.html No
10 RAT HEART-2DPAGE 2-DE database of rat heart http://www.mpiib-berlin.mpg.de/2D-PAGE/RAT-HEART/2d/ No
11 SIENA-2DPAGE 2D-PAGE database (Chlamydia trachomatis, Caenorhabditis elegans, Human breast ductal carcinoma and histologically normal tissue, Human amniotic fluid) http://www.bio-mol.unisi.it/2d/2d.html No

2. Subcellular Location Databases

S. No Name Description Link Standalone Available
1 eSLDB collects the annotations of subcellular localizations of eukaryotic proteomes based on experimental results, homology, and computational predictions. http://gpcr.biocomp.unibo.it/esldb/index.htm No
2 PSORTdb A two-component searchable and browsable database. ePSORTdb contains bacterial proteins of experimentally verified localization used in training and testing of PSORTb. cPSORTdb contains predictions of localization for bacterial genomes. http://db.psort.org/ no
3 SUBA an Arabidopsis subcellular localization database with annotations based on experimental results, literature references, Swiss-Prot annotations, and computational predictions. http://www.plantenergy.uwa.edu.au/applications/suba2/ No
4 FTFLP Database contains a collection of Arabidopsis protein localizations verified using fluorescent tagging of full-length proteins. http://gfp.stanford.edu/cgi-bin/search_database.cgi No
5 SPdb a signal peptide database containing a repository of experimentally verified and predicted signal peptides. http://proline.bic.nus.edu.sg/spdb/ No
6 NESbase a database with a collection of nuclear export signals. http://www.cbs.dtu.dk/databases/NESbase/ No
7 LOCATE a database that houses data describing the membrane organization and subcellular localization of human and mouse proteins. http://locate.imb.uq.edu.au/ No
8 PDBTM a database of transmembrane proteins with known 3D structures. http://pdbtm.enzim.hu/ No
9 PA-GOSUB a database collecting the localization predictions made by the Proteome Analyst tool. http://www.cs.ualberta.ca/%7Ebioinfo/PA/GOSUB/ No
10 Organelle DB a database of eukaryotic proteins found at various organelles and subcellular structures. http://organelledb.lsi.umich.edu/ No
11 AMPDB A database of known and predicted mitochondrial proteins in the plant species Arabidopsis thaliana. http://www.plantenergy.uwa.edu.au/applications/ampdb/index.html No
12 MITOMAP a database of information related to the human mitochondrial genome. http://www.mitomap.org/ No
13 DBSubLoc A dataset of proteins with annotated subcellular localizations according to SWISS-PROT and PIR. http://www.bioinfo.tsinghua.edu.cn/dbsubloc.html No
14 LOCtarget a database of LOCtree predictions for structural genomics targets. http://www.rostlab.org/services/LOCtarget/ No
15 LOC3d a database of predicted localizations for eukaryotic proteins with 3D structures. http://cubic.bioc.columbia.edu/db/LOC3d/ No
16 LOCkey contains predicted localizations for the human, Arabidopsis, fly, yeast and worm genomes based on Swiss-Prot keywords. http://cubic.bioc.columbia.edu/db/LOCkey/ No
17 LOChom is a database of predicted localizations based on homology to experimentally annotated proteins. http://cubic.bioc.columbia.edu/db/LOChom/ No
18 signalp The dataset of prokaryotic and eukaryotic secreted and non-secreted proteins used to train SignalP, and also used to train PSORTb's signal peptide prediction module. http://www.cbs.dtu.dk/ftp/signalp/ No
19 Signal Peptides The dataset of prokaryotic and eukaryotic secreted and non-secreted proteins used in an independent evaluation of several signal peptide prediction methods, and used to test PSORTb's signal peptide prediction module ftp://ftp.ebi.ac.uk/pub/contrib/swissprot/testsets/signal/ No

3. Post-translation Modifications Databases

S. No Name Description Link Standalone Available
1 PRENbase Database of Prenylated Proteins http://mendel.imp.ac.at/sat/PrePS/PRENbase/ No