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http://www.imtech.res.in/raghava/hslpred/

A support vector machine (SVM)-based method for the prediction of 4 major subcellular localization (cytoplasm, mitochondrial, nuclear and plasma membrane) of human proteins using various features such as i) amino acid composition, ii) dipeptide composition and iii) evolutionary information of proteins.

Proper citation: HSLPred (RRID:SCR_011972) Copy   

•   Source: SciCrunch Registry

http://jci-bioinfo.cn/iLoc-Plant

Data analysis service for predicting subcellular localization of plant proteins with single and multiple sites.

Proper citation: iLoc-Plant (RRID:SCR_011973) Copy   

•   Source: SciCrunch Registry

http://bio-cluster.iis.sinica.edu.tw/kbloc/index.html

A knowledge-based data analysis service to predict the localization site(s) of both single-localized and multi-localized proteins.

Proper citation: KnowPredsite (RRID:SCR_011974) Copy   

•   Source: SciCrunch Registry

http://bleoberis.bioc.cam.ac.uk/mcsm

Data analysis service to the study of missense mutations which relies on graph-based signatures.

Proper citation: mCSM (RRID:SCR_010776) Copy   

•   Source: SciCrunch Registry

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

A predictor for the subcellular localization of proteins in eukaryotes that 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. BaCelLo's predictions are balanced among different classes and all the localizations are considered as equiprobable.

Proper citation: BaCelLo (RRID:SCR_011965) Copy   

•   Source: SciCrunch Registry

http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc/

A package of web-servers for predicting subcellular localization of proteins in different organisms.

Proper citation: Cell-PLoc (RRID:SCR_011966) Copy   

•   Source: SciCrunch Registry

http://cello.life.nctu.edu.tw/

A subCELlular LOcalization predictor based on a multi-class support vector machine (SVM) classification system. CELLO uses 4 types of sequence coding schemes: the amino acid composition, the di-peptide composition, the partitioned amino acid composition and the sequence composition based on the physico-chemical properties of amino acids. They combine votes from these classifiers and use the jury votes to determine the final assignment.

Proper citation: CELLO (RRID:SCR_011968) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

•   Source: SciCrunch Registry

http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

•   Source: SciCrunch Registry

http://www.antibodypedia.com/

Open-access database of antibodies against human proteins developed through collaboration between Antibodypedia AB and the Nature Publishing Group. It aims to provide the scientific community and antibody distributors alike with information on the effectiveness of specific antibodies in specific applications--to help scientists select the right antibody for the right application. Antibodypedia's mission is to promote the functional understanding of the human proteome and expedite analysis of potential biomarkers discovered through clinical efforts. To this end, they have developed an open-access, curated, searchable database containing annotated and scored affinity reagents to aid users in selecting antibodies tailored to specific biological and biomedical assays. They envisage Antibodypedia as a virtual repository of validated antibodies against all human, and ultimately most model-organism, proteins. Such a tool will be exploitable to identify affinity reagents to document protein expression patterns in normal and pathological states and to purify proteins alone and in complex for structural and functional analyses. They hope to promote characterization of the roles and interplay of proteins and complexes in human health and disease. They encourage commercial providers to submit information regarding their inventory of antibodies with links to quality control data. Independent users can submit their own application-specific experimental data using standard validation criteria (supportive or non-supportive) developed with the assistance of an international advisory board recruited from academic research institutions. Users can also comment on specific antibodies without submitting validation data.

Proper citation: Antibodypedia (RRID:SCR_012782) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/glycomics/gt/gtdb.shtml

A pathway-based graphical interface for navigating the glycoenzyme database. The goal of the project is to define the paradigms by which carbohydrate binding proteins function in cellular communication. These pages are divided into six categories: -Glycosphingolipid: Sub-categories are Isogloboseries, Globoseries, Neo-lactoseries, Lactoseries and Ganglioseries - N-linked: Sub-categories are High-mannose, Hybrid and Complex -Mucin -Terminal Core 1 -Other O-linked -Terminal All: Includes all potential terminal structures for each glycan category

Proper citation: Glycosylation Pathways Database (RRID:SCR_013486) Copy   

•   Source: SciCrunch Registry

http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

The Therapeutically Relevant Multiple Pathways Database is designed to provide information about such multiple pathways and related therapeutic targets described in the literatures, the targeted disease conditions, and the corresponding drugs/ligands directed at each of these targets. This database currently contains 11 entries of multiple pathways, 97 entries of individual pathways, 120 targets covering 72 disease conditions along with 120 sets of drugs directed at each of these targets. Each entry can be retrieved through multiple methods including multiple pathway name, individual pathway name and disease name. Additional information provided include protein name, synonyms, Swissprot AC number, species, gene name and location, protein sequence (AASEQ) and gene sequence (NTSEQ) as well as potential therapeutic implications while applicable. Cross-links to other databases are provided which include Genecard, GDB, Locuslink, NCBI, KEGG, OMIM, SwissProt to facilitate the access of more detailed information about various aspects of the particular target or non-target protein. Queries can be submitted by entering or selecting the required information in any one or combination of the fields in the form. User can specify full name or any part of the name in a text field, or choose one item from an selection field. Sponsors: TRMP is supported by the National University of Singapore.

Proper citation: Therapeutically Relevant Multiple Pathways Database (RRID:SCR_013471) Copy   

•   Source: SciCrunch Registry

http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html

Cube-DB is a database of pre-evaluated conservation and specialization scores for residues in paralogous proteins belonging to multi-member families of human proteins. Protein family classification follows (largely) the classification suggested by HUGO Gene Nomenclature Committee. Sets of orhtologous protein sequences were generated by mutual-best-hit strategy using full vertebrate genomes available in Ensembl. The scores, described on documentation page, are assigned to each individual residue in a protein, and presented in the form of a table (html or downloadable xls formats) and mapped, when appropriate, onto the related structure (Jmol, Pymol, Chimera).

Proper citation: Cube-DB (RRID:SCR_013233) Copy   

•   Source: SciCrunch Registry

http://www.alzforum.org/res/com/ant/

The Alzheimer Research Forum is the web''s most dynamic scientific community dedicated to understanding Alzheimer''s disease and related disorders. It also contains a database of providers of antibodies directed against several hundred molecules and proteins of relevant to research on Alzheimer and other neurodegenerative diseases. The web site reports on the latest scientific findings, from basic research to clinical trials; creates and maintains public databases of essential research data and reagents, and produces discussion forums to promote debate, speed the dissemination of new ideas, and break down barriers across the numerous disciplines that can contribute to the global effort to cure Alzheimer''s disease. The ARF team of professional science writers and editors, information technology experts, web developers and producers all work closely with our distinguished and diverse Advisory Board to ensure a high-quality of information and services. We very much welcome our readers'' participation in all aspects of the web site. Sponsors: The Alzheimer Research Forum is an independent nonprofit organization. It is supported by grants and individual donations.

Proper citation: Alzforum Antibody Directory for Neuroscience Research (RRID:SCR_013601) Copy   

•   Source: SciCrunch Registry

http://research.bioinformatics.udel.edu/iptmnet/

A protein database which connects multiple disparate bioinformatics tools and systems text mining, data mining, analysis and visualization tools, and databases and ontologies.

Proper citation: iPTMnet (RRID:SCR_014416) Copy   

•   Source: SciCrunch Registry

https://pharos.nih.gov/idg/index#

Database of ligands and diseases. Its goal is to develop a knowledge-base for the Druggable Genome (DG) in order to illuminate the uncharacterized and/or poorly annotated portion of the genome. DG, focusing on four of the most commonly drug-targeted protein families: G-protein-coupled receptors (GPCRs); nuclear receptors (NRs); ion channels (ICs); and kinases.

Proper citation: PHAROS (RRID:SCR_016258) Copy   

•   Source: SciCrunch Registry

http://p300db.choudharylab.org

Data collection of CBP/p300 regulated acetylome, proteome, and transcriptome in murine embryonic fibroblasts. Composed of Symbol search for quantified acetylation sites, proteins and transcripts abundance in CBP/p300, Domain search for batch query of proteins by specific domain and Conserved sites for acetylation sites that are conserved between mouse and human, and their regulation in KATi treated cells.

Proper citation: p300db (RRID:SCR_017063) Copy   

•   Source: SciCrunch Registry

https://www.expasy.org/resources/uniprotkb-swiss-prot

Curated component of UniProtKB (produced by the UniProt consortium). It contains hundreds of thousands of protein descriptions, including function, domain structure, subcellular location, post-translational modifications and functionally characterized variants.

Proper citation: UniProtKB/Swiss-Prot (RRID:SCR_021164) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/pubs/MitoCarta/

Collection of genes encoding proteins with strong support of mitochondrial localization. Inventory of genes encoding mitochondrial-localized proteins and their expression across 14 mouse tissues. Database is based on human and mouse RefSeq proteins that are mapped to NCBI Gene loci. MitoCarta 2.0 inventory provides molecular framework for system-level analysis of mammalian mitochondria.

Proper citation: MitoCarta (RRID:SCR_018165) Copy   

•   Source: SciCrunch Registry

http://www.ucl.ac.uk/biobank/

Two University College London (UCL) biobanks, one based at the Royal Free Hospital (RFH) Campus and the other based at Bloomsbury supporting Pathology and the Cancer Institute, will act as physical repositories for collections of biological samples and data from patients consented at UCLH, Partners Hospitals and external sources. This will incorporate collections of existing stored samples and new collections. UCL-RFH BioBank, the physical repository at the Royal Free, presents a unique opportunity to advance medical research through making access to research tissue easier, faster and much more efficient. The BioBank is both a physical repository, with capacity for up to 1 million cryogenically stored samples and a virtual repository for all tissue, cell, plasma, serum, DNA and RNA samples stored throughout UCLP. In particular, samples considered "relevant material", such as tissues and cells, that are licensed by the Human Tissue Authority, can be stored long term. Existing holdings of tissues and cells where appropriate can be transferred to the Physical BioBank at the Royal Free. UCL - Royal Free BioBank provides a flexible approach to banking, allowing the Depositor to pick and choose services that are tailored to fit their requirements. Collaborations arising from publicizing of the existence of the holdings are entirely at the discretion of the depositor, as the facility ensures that access to the deposits remains at the decision of the Depositor/User. UCL Biobank for studying Health and Disease (based at Pathology-Rockefeller building and the UCL-Cancer Institute will support projects principally involved in the study of human disease. The aim is to support primarily, research in the Pathology Department, UCLH and the UCL-Cancer Institute but it will also support other UCLH partners. The biobank will store normal and pathological specimens, surplus to diagnostic requirements, from relevant tissues and bodily fluids. Stored tissues will include; snap-frozen or cryopreserved tissue, formalin-fixed tissue, paraffin-embedded tissues, and slides prepared for histological examination. Tissues will include resection specimens obtained surgically or by needle core biopsy. Bodily fluids will include; whole blood, serum, plasma, urine, cerebrospinal fluid, milk, saliva and buccal smears and cytological specimens such as sputum and cervical smears. Fine needle aspirates obtained from tissues and bodily cavities (e.g. pleura and peritoneum) will also be collected. Where appropriate the biobank will also store separated cells, protein, DNA and RNA isolated from collected tissues and bodily fluids described above. Some of the tissue and aspirated samples will be stored in the diagnostic archive.

Proper citation: UCL Biobank (RRID:SCR_000517) Copy   

•   Source: SciCrunch Registry