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DBSubLoc - Database of protein Subcellular Localization

http://www.bioinfo.tsinghua.edu.cn/dbsubloc.html

Description :
Database of protein subcellular localization

eSLDB - eukaryotic Subcellular Localization database

http://gpcr.biocomp.unibo.it/esldb

Description :
eSLDB (eukaryotic Subcellular Localization DataBase) collects the annotations of subcellular localization of eukaryotic proteomes. For each sequence, the database lists localization obtained adopting three different approaches: 1) experimentally determined (when available); 2) homology based (when possible); 3) predicted. The latter is computed with a suite of machine learning based methods, developed in house. All the data are available at our website and can be searched by sequence, by protein code and/or by protein description. Furthermore a more complex search can be performed combining different search fields and keys. All the data contained in the database can be freely downloaded in flat file format.

Aknowledgement :
RC acknowledges the receipt of the following grants: PNR 2001-2003 (FIRB art.8) for a project on Bioinformatics for Genomics and Proteomics, a FIRB 2003 LIBI-International Laboratory of Bioinformatics and the support to the Bologna node of the Biosapiens Network of Excellence project within the European Union’s VI Framework Programme (contract number LSHG-CT-2003-503265). PF acknowledges MIUR for a grant on Proteases. AP and PLM are supported by a FIRB 2003-LIBI grant.

References :
1. Pierleoni A, Martelli PL, Fariselli P, Casadio R (2007) eSLDB: eukaryotic Subcellular Localization DataBase. Nucleic Acids Res. 35: in press

NOPdb: Nucleolar Proteome Database

http://www.lamondlab.com/NOPdb/

Description :
The Nucleolar Proteome Database (NOPdb) archives data on more than 700 proteins that were identified by multiple mass spectrometry (MS) analyses from highly purified preparations of human nucleoli, the most prominent nuclear organelle. Each protein entry is annotated with information about its corresponding gene, its domain structures and relevant protein homologues across species, as well as documenting its MS identification history including all the peptides sequenced by tandem MS/MS. Moreover, data showing the quantitative changes in the relative levels of ~500 nucleolar proteins are compared at different timepoints upon transcriptional inhibition. Correlating changes in protein abundance at multiple timepoints, highlighted by visualization means in the NOPdb, provides clues regarding the potential interactions and relationships between nucleolar proteins and thereby suggests putative functions for factors within the 30% of the proteome which comprises novel/ uncharacterized proteins. The NOPdb (http://www.lamondlab.com/NOPdb) is searchable by either gene names, protein sequences, Gene Ontology terms or motifs, or by limiting the range for isoelectric points and/or molecular weights and links to other databases (e.g. LocusLink, OMIM and PubMed).

Recent develoments :
The database is currently also searchable by mRNA sequences or by short amino acid sequences. Moreover, we planned to include an online-documentation to help users to surf through the site and additional kinetic profiles for each protein, based on their responses to both different drug treatments and other metabolic and cell cycle variations.

Aknowledgement :
The Human Frontier Science Program is acknowledged for a research grant entitled 'Functional organization of the cell nucleus investigated through proteomics and molecular dynamics’. We thank many colleagues working diligently to explore the dynamic nucleolar proteome in the ongoing collaboration between the laboratories of Angus I Lamond (University of Dundee) and Matthias Mann (University of Southern Denmark)

References :
1. Andersen, J.S., Lyon, C.E., Fox, A.H., Leung, A.K., Lam, Y.W., Steen, H., Mann, M. and Lamond, A.I. (2002) Directed proteomic analysis of the human nucleolus. Curr Biol, 12, 1-11.
2.Leung, A.K., Andersen, J.S., Mann, M. and Lamond, A.I. (2003) Bioinformatic analysis of the nucleolus. Biochem J, 376, 553-569.

NPD - Nuclear Protein Database

http://npd.hgu.mrc.ac.uk/

Description :
The NPD is a curated database that contains information on more than 1200 vertebrate proteins that are thought, or are known, to localise to the cell nucleus. Each entry is annotated with information on predicted protein size and isoelectric point, as well as any repeats, motifs or domains within the protein sequence. In addition, information on the sub-nuclear localisation of each protein is provided and the biological and molecular functions are described using Gene Ontology (GO) terms. The database is searchable by keyword, protein name, sub-nuclear compartment and protein domain/motif. Links to other databases are provided (e.g. Entrez, SWISS-PROT, OMIM, PubMed, PubMed Central). Thus, NPD provides a gateway through which the nuclear proteome may be explored. The database can be accessed at http://npd.hgu.mrc.ac.uk and is updated monthly.

Aknowledgement :
We would like to acknowledge the help of MRC HGU computing services and Dr. Heidi Sutherland for comments and data entry during the development of NPD. We especially thank all colleagues who have contributed to the development and information content of NPD. The NPD was made possible by funding from the Medical Research Council (UK) and the James S. McDonnell Foundation. GD was supported by a fellowship from the Canadian Institutes of Health Research (CIHR) and WAB is a Centennial Fellow of the James S. McDonnell Foundation.

References :
Bickmore, WA and HGE Sutherland (2002) Addressing protein localization within the nucleus EMBO J. 21(6):1248-1254.
Sutherland HG, Mumford GK, Newton K, Ford LV, Farrall R, Dellaire G, Caceres JF, Bickmore WA. (2001) Large-scale identification of mammalian proteins localized to nuclear sub-compartments. Hum Mol Genet. 10(18):1995-2011.
Tate P, Lee M, Tweedie S, Skarnes WC, Bickmore WA. (1998) Capturing novel mouse genes encoding chromosomal and other nuclear proteins. J Cell Sci. 111 (17):2575-85.

THGS - Transmembrane Helices in Genome Sequences

http://pranag.physics.iisc.ernet.in/thgs/

Description :
Predicted transmembrane proteins

TopDB

http://topdb.enzim.hu/

Description :
Topology Data Bank of transmembrane proteins

TransMembrane Protein DataBase

http://bioinfo.si.hirosaki-u.ac.jp/~TMPDB/

Description :
TransMembrane Protein DataBase, TMPDB (http://bioinfo.si.hirosaki-u.ac.jp/~TMPDB/) is a collection of transmembrane proteins with topologies based on definite experimental evidences such as X-ray crystallography, NMR, gene fusion technique, substituted cysteine accessibility method, Asp(N)-linked glycosylation experiment and other biochemical methods. TMPDB would serve the requirements of both bioinformaticians and biologists, as a test and/or training dataset, for improving the existing TM topology prediction methods and developing novel prediction methods with higher performance as well as for making better understanding of TM proteins physicochemically.

TMFunction

http://tmbeta-genome.cbrc.jp/TMFunction/

Description :
We have developed the database TMFunction, which is a collection of more than 2900 experimentally observed functional residues in membrane proteins. Each entry includes the numerical values for the parameters IC50 (measure of the effectiveness of a compound in inhibiting biological function), Vmax (maximal velocity of transport), relative activity of mutants with respect to wild type protein, binding affinity, dissociation constant, etc., which are important for understanding the sequence-structure-function relationship of membrane proteins. In addition, we have provided information about the name and source of the protein, Uniprot and Protein Data Bank codes, mutational and literature information. Furthermore, TMFunction is linked to related databases and other resources. We have set up a web interface with different search and display options so that users have the ability to get the data in several ways. TMFunction is freely available.

PhyloFacts

http://phylogenomics.berkeley.edu/phylofacts/

Description :
The PhyloFacts resource contains pre-calculated structural and phylogenomic analysis of over 15,000 protein family "books" across the Tree of Life. Each book includes a multiple sequence alignment, one or more phylogenetic trees, predicted subfamilies, predicted 3D protein structures, active sites and other key residues, cellular localization, and Gene Ontology (GO) annotations and evidence codes. PhyloFacts includes hidden Markov models for classification of user-submitted (DNA or protein) sequences to protein families and subfamilies. Our current focus is on covering all the gene families represented in the human genome and all structural domains, but plan to expand the resource to include all proteins in all species. PhyloFacts enables biologists to avoid the systematic errors associated with function prediction by homology through the integration of a variety of experimental data and bioinformatics methods in an evolutionary framework.

Aknowledgement :
This work was supported by a Presidential Early Career Award for Scientists and Engineers (PECASE) from the National Science Foundation, and by an RO1 from the National Human Genome Research Institute of the NIH.

References :
1. Krishnamurthy, N., Brown, D., Kirshner, D. and Sjölander, K. (2006). PhyloFacts: An online structural phylogenomic encyclopedia for protein functional and structural classification. Genome Biology, 7(9):R83.

PDB_TM

http://pdbtm.enzim.hu/

Description :
Integral membrane proteins play important roles in living cells. Although these proteins are estimated to constitute around 25% of proteins at a genomic scale, the Protein Data Bank (PDB, http://www.rcsb.org/pdb) contains only a few hundred membrane proteins due to the difficulties with experimental techniques. The presence of transmembrane proteins in the structure data bank, however, is quite invisible, as the annotation of these entries is rather poor. Even if a protein is identified as a transmembrane one, the possible location of the lipid bilayer is not indicated in the PDB because these proteins are crystallized without their natural lipid bilayer.
In PDB_TM database we have collected all transmembrane proteins from PDB by using the TMDET (http://www.enzim.hu/TMDET) algorithm developed earlier. The possible localization of membrane plane is also determined together with the sequential localization of membraneaous part of the protein. These assigments are based on the TMDET algorithm as well, which uses structural information only to locate the most likely position of the lipid bilayer. By using TMDET algorithm, the PDB_TM database is automatically updated every week, keeping it synchronized with the latest PDB updates.

Aknowledgement :
This work has been sponsored by grants BIO-0005/2001, OTKA T34131, D42207 and F043609. Zs.D. and G.E.T. were supported by the Bolyai Janos Scholarship.

LOCtarget

http://www.rostlab.org/services/LOCtarget/

Description :
LOCtarget is a tool for predicting, and a database of pre-computed predictions for, sub-cellular localization of eukaryotic and prokaryotic proteins. Several methods are employed to make the predictions, including text analysis of SWISS-PROT keywords, nuclear localization signals, and the use of neural networks.

Proteome Analyst

http://www.cs.ualberta.ca/~bioinfo/PA/

Description :
Proteome Analyst is a high-throughput tool for predicting properties for each protein in a proteome. The user provides a proteome in fasta format, and the system employs Psi-blast, Psipred and Modeller to predict protein function and subcellular localization. Proteome Analyst uses machine-learned classifiers to predict things such as GO molecular function. User-supplied training data can also be used to create custom classifiers.

SUBA

http://www.suba.bcs.uwa.edu.au/

Description :
The Arabidopsis Subcellular Database (SUBA, http://www.suba.bcs.uwa.edu.au) is maintained by the ARC Centre of Excellence in Plant Energy Biology at The University of Western Australia. The database contains publicly available protein subcellular localisation data from a variety of sources from the model plant Arabidopsis. The database can be relationally interrogated through a purpose built web interface that enables powerful SQL queries to be formulated against the datasets. Localisation information include data from chimeric fluorescent fusion protein studies, large scale proteomic analyses of subcellular compartments, literature and homology information (Gene Ontology annotations, Swiss-Prot and gene descriptors) and pre-computed bioinformatic prediction of localisation by 10 software packages. These data provide non-redundant subcellular localisation information on approximately 7000 Arabidopsis proteins and bioinformatic localisation information for all ~30,000 proteins in the database.

LOCATE

http://locate.imb.uq.edu.au/

Description :
LOCATE is a curated, web-accessible database that houses data describing the membrane organization and subcellular localization of proteins from the FANTOM3 Isoform Protein Sequence set (1). Membrane organization is predicted by the high-throughput, computational pipeline MemO. The subcellular locations of selected proteins from this set were determined by a high-throughput, immunofluorescence-based assay and by manually reviewing over 1700 peer-reviewed publications. LOCATE represents the first effort to catalogue the experimentally-verified subcellular location and membrane organization of mammalian proteins using a high-throughput approach and provides localization data for nearly 40% of the mouse proteome.

Aknowledgement :
The authors would like to acknowledge Nicholas Hamilton for implementing DomainDraw, the domain drawing program; Robert Luetterforst for assistance with the literature mining; and Emma Redhead for designing the LOCATE XML schema and XML document generator. The work was supported by funds from the Australian Research Council (ARC) and by the Research Grant for the RIKEN Genome Exploration Research Project from the Ministry of Education, Culture, Sports, Science and Technology of the Japanese Government to YH, and the Research Grant for the Genome Network Project from the Ministry of Education, Culture, Sports, Science and Technology of the Japanese Government. RDT is supported by a National Health and Medical Research Council of Australia R. Douglas Wright Career Development Award. RNA is supported by a Postgraduate Research Scholarship from the IMB, University of Queensland. MJD is supported by the National Institute for Diabetes, Digestion and Kidney Disease, National Institutes of Health (DK63400) as part of the Stem Cell Genome Anatomy Project (http://www.scgap.org/).

References :
1. Carninci, P., Kasukawa, T., Katayama, S., Gough, J., Frith, M.C. et al. (2005) The transcriptional landscape of the mammalian genome. Science, 309, 1559-1563.

MiCroKit

http://bioinformatics.lcd-ustc.org/microkit/

Description :
Based on the rationale of "seeing is believing", we have collected proteins known to be localized in midbody, centrosome, and/or kinetochore from the literature into this database, MiCroKit. All collected proteins have supportive evidences for subcellular localizations under fluorescent microscope unambiguously. The current version MiCroKit 2.0 provides detailed information for 1,120 such proteins from seven model organisms, including budding & fission yeast, nematode, fruit fly, frog/Xenopus, mouse and human. MiCroKit is accessible from http://bioinformatics.lcd-ustc.org/microkit/ or http://csbl.bmb.uga.edu/~ffzhou/microkit/.

Aknowledgement :
The work is supported, in part, by Chinese Natural Science Foundation (39925018, 30270654 and 30270293), Chinese Academy of Science (KSCX2-2-01), Chinese 973 project (2002CB713700), Chinese Minister of Education (20020358051), American Cancer Society (RPG-99-173-01) and National Institutes of Health (DK56292; CA92080). X. Yao is a Georgia Cancer Coalition Eminent Scholar. F. Zhou and Y. Xu’s work is supported, in part, by the Georgia Cancer Coalition under a “Distinguished Scholar” grant, and National Science Foundation (NSF/DBI-0354771, NSF/ITR-IIS-0407204).

References :
1. Xue Y, Zhou F, Fu C, Jin C, Pei S, Xu Y, Yao X. MiCroKit: An Integrated Database of Midbody, Centrosome and Kinetochore. Submitted.

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