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http://depts.washington.edu/yeastrc/

Biomedical technology research center that (1) exploits the budding yeast Saccharomyces cerevisiae to develop novel technologies for investigating and characterizing protein function and protein structure (2) facilitates research and extension of new technologies through collaboration, and (3) actively disseminates data and technology to the research community. Through collaboration, the YRC freely provides resources and expertise in six core technology areas: Protein Tandem Mass Spectrometry, Protein Sequence-Function Relationships, Quantitative Phenotyping, Protein Structure Prediction and Design, Fluorescence Microscopy, Computational Biology.

Proper citation: Yeast Resource Center (RRID:SCR_007942) Copy   

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http://www.euroscarf.de/index.php?name=News

Archive of yeast strains and plasmids that were generated during various yeast functional analysis projects.

Proper citation: EUROpean Saccharomyces Cerevisiae ARchive for Functional Analysis (RRID:SCR_003093) Copy   

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http://ophid.utoronto.ca/i2d

Database of known and predicted mammalian and eukaryotic protein-protein interactions, it is designed to be both a resource for the laboratory scientist to explore known and predicted protein-protein interactions, and to facilitate bioinformatics initiatives exploring protein interaction networks. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered predictions. It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. It contains 490,600 Source Interactions, 370,002 Predicted Interactions, for a total of 846,116 interactions, and continues to expand as new protein-protein interaction data becomes available.

Proper citation: I2D (RRID:SCR_002957) Copy   

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http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

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http://www.reactome.org

Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.

Proper citation: Reactome (RRID:SCR_003485) Copy   

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http://www.GeneWeaver.org

Freely accessible phenotype-centered database with integrated analysis and visualization tools. It combines diverse data sets from multiple species and experiment types, and allows data sharing across collaborative groups or to public users. It was conceived of as a tool for the integration of biological functions based on the molecular processes that subserved them. From these data, an empirically derived ontology may one day be inferred. Users have found the system valuable for a wide range of applications in the arena of functional genomic data integration.

Proper citation: Gene Weaver (RRID:SCR_003009) Copy   

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http://www.ideal.force.cs.is.nagoya-u.ac.jp/IDEAL/

IDEAL, Intrinsically Disordered proteins with Extensive Annotations and Literature, is a collection of knowledge on experimentally verified intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). IDEAL contains manually curated annotations on IDPs in locations, structures, and functional sites such as protein binding regions and posttranslational modification sites together with references and structural domain assignments. Protean segment One of the unique phenomena seen in IDPs is so-called the coupled folding and binding, where a short flexible segment can bind to its binding partner with forming a specific structure to act as a molecular recognition element. IDEAL explicitly annotates these regions as protean segment (ProS) when unstructured and structured information are both available in the region. Access to the data All the entries are tabulated in the list and individual entries can be retrieved by using the search tool at the upper-right corner in this page. IDEAL also provides the BLAST search, which can find homologs in IDEAL. All the information in IDEAL can be downloaded in the XML file.

Proper citation: IDEAL - Intrinsically Disordered proteins with Extensive Annotations and Literature (RRID:SCR_006027) Copy   

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http://www.yeastgenome.org/

A curated database that provides comprehensive integrated biological information for Saccharomyces cerevisiae along with search and analysis tools to explore these data. SGD allows researchers to discover functional relationships between sequence and gene products in fungi and higher organisms. The SGD also maintains the S. cerevisiae Gene Name Registry, a complete list of all gene names used in S. cerevisiae which includes a set of general guidelines to gene naming. Protein Page provides basic protein information calculated from the predicted sequence and contains links to a variety of secondary structure and tertiary structure resources. Yeast Biochemical Pathways allows users to view and search for biochemical reactions and pathways that occur in S. cerevisiae as well as map expression data onto the biochemical pathways. Literature citations are provided where available.

Proper citation: SGD (RRID:SCR_004694) Copy   

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http://swissregulon.unibas.ch/fcgi/sr/swissregulon

A database of genome-wide annotations of regulatory sites. The predictions are based on Bayesian probabilistic analysis of a combination of input information including: * Experimentally determined binding sites reported in the literature. * Known sequence-specificities of transcription factors. * ChIP-chip and ChIP-seq data. * Alignments of orthologous non-coding regions. Predictions were made using the PhyloGibbs, MotEvo, IRUS and ISMARA algorithms developed in their group, depending on the data available for each organism. Annotations can be viewed in a Gbrowse genome browser and can also be downloaded in flat file format.

Proper citation: SwissRegulon (RRID:SCR_005333) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 22,2022. database of protein subcellular localization annotation for eukaryotic organisms. It contains experimental annotations derived from primary protein databases, homology based annotations and computational predictions.

Proper citation: eSLDB - eukaryotic Subcellular Localization database (RRID:SCR_000052) Copy   

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http://lifespandb.sageweb.org/

Database that collects published lifespan data across multiple species. The entire database is available for download in various formats including XML, YAML and CSV.

Proper citation: Lifespan Observations Database (RRID:SCR_001609) Copy   

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http://mint.bio.uniroma2.it/

A database that focuses on experimentally verified protein-protein interactions mined from the scientific literature by expert curators. The curated data can be analyzed in the context of the high throughput data and viewed graphically with the MINT Viewer. This collection of molecular interaction databases can be used to search for, analyze and graphically display molecular interaction networks and pathways from a wide variety of species. MINT is comprised of separate database components. HomoMINT, is an inferred human protein interatction database. Domino, is database of domain peptide interactions. VirusMINT explores the interactions of viral proteins with human proteins. The MINT connect viewer allows you to enter a list of proteins (e.g. proteins in a pathway) to retrieve, display and download a network with all the interactions connecting them.

Proper citation: MINT (RRID:SCR_001523) Copy   

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http://www.uniprot.org/

Collection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.

Proper citation: UniProt (RRID:SCR_002380) Copy   

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http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

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http://the_brain.bwh.harvard.edu/uniprobe/

Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences.

Proper citation: UniPROBE (RRID:SCR_005803) Copy   

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http://gtlinker.cnb.csic.es/

Web application that filters and links enriched output data identifying sets of associated genes and terms, producing metagroups of coherent biological significance. The method uses fuzzy reciprocal linkage between genes and terms to unravel their functional convergence and associations. It can also be accessed through its web service.

Proper citation: GeneTerm Linker (RRID:SCR_006385) Copy   

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http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

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http://clipserve.clip.ubc.ca/topfind

An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data

Proper citation: TopFIND (RRID:SCR_008918) Copy   

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http://www.textpresso.org/

An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.

Proper citation: Textpresso (RRID:SCR_008737) Copy   

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http://proteome.gs.washington.edu/software/bibliospec/documentation/index.html

BiblioSpec enables the identification of peptides from tandem mass spectra by searching against a database of previously identified spectra. This suite of software tools is for creating and searching MS/MS peptide spectrum libraries. BiblioSpec is available free of charge for noncommercial use through an interactive web-site at http://depts.washington.edu/ventures/UW_Technology/Express_Licenses/bibliospec.php The BiblioSpec package contains the following programs: * BlibBuild creates a library of peptide MS/MS spectra from MS2 files. * BlibFilter removes redundant spectra from a library. * BlibSearch searches a spectrum library for matches to query spectra, reporting the results in an SQT file. In addition to the primary programs, the following auxiliary programs are available: * BlibStats writes summary statistics describing a library. * BlibToMS2 writes a library in MS2 file format. * BlibUpdate adds, deletes, or annotates spectra. * BlibPpMS2 processes spectra (bins peaks, removes noise, normalizes intensity) as done in BlibSearch and prints the resulting spectra to a text file. Several reference libraries are available for download. These libraries are updated regularly and are for use under the Linux operating system. You will find libraries for * Escherichia coli * Saccharomyces cerevisiae * Caenorhabditis elegans

Proper citation: BiblioSpec (RRID:SCR_004349) Copy   

•   Source: SciCrunch Registry