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http://iubio.bio.indiana.edu/webapps/SeWeR/

Sequence analysis using Web Resources (SeWeR) is an integrated, Dynamic HTML (DHTML) interface to commonly used bioinformatics services available on the World Wide Web. It is highly customizable, extendable, platform neutral, completely server-independent and can be hosted as a web page as well as being used as stand-alone software running within a web browser. It doesn''t require any server to host itself. The goal of SeWeR is to turn your web-browser into a powerful sequence-analysis tool. It is written entirely in JavaScript1.2. SeWeR can be downloaded and mirrored freely. The whole package is just around 300K. You can even run it from a floppy. SeWeR is not compatible with Netscape 6. SeWeR now generates graphics. Savvy is a plasmid drawing software that generates plasmid map in the revolutionary Scalable Vector Graphics format from W3C.

Proper citation: SeWeR - SEquence analysis using WEb Resources (RRID:SCR_004167) Copy   

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http://nematode.lab.nig.ac.jp/

Expression pattern map of the 100Mb genome of the nematode Caenorhabditis elegans through EST analysis and systematic whole mount in situ hybridization. NEXTDB is the database to integrate all information from their expression pattern project and to make the data available to the scientific community. Information available in the current version is as follows: * Map: Visual expression of the relationships among the cosmids, predicted genes and the cDNA clones. * Image: In situ hybridization images that are arranged by their developmental stages. * Sequence: Tag sequences of the cDNA clones are available. * Homology: Results of BLASTX search are available. Users of the data presented on our web pages should not publish the information without our permission and appropriate acknowledgment. Methods are available for: * In situ hybridization on whole mount embryos of C.elegans * Protocols for large scale in situ hybridization on C.elegans larvae

Proper citation: NEXTDB (RRID:SCR_004480) Copy   

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http://stemcellcommons.org/

Open source environment for sharing, processing and analyzing stem cell data bringing together stem cell data sets with tools for curation, dissemination and analysis. Standardization of the analytical approaches will enable researchers to directly compare and integrate their results with experiments and disease models in the Commons. Key features of the Stem Cell Commons * Contains stem cell related experiments * Includes microarray and Next-Generation Sequencing (NGS) data from human, mouse, rat and zebrafish * Data from multiple cell types and disease models * Carefully curated experimental metadata using controlled vocabularies * Export in the Investigation-Study-Assay tabular format (ISA-Tab) that is used by over 30 organizations worldwide * A community oriented resource with public data sets and freely available code in public code repositories such as GitHub Currently in development * Development of Refinery, a novel analysis platform that links Commons data to the Galaxy analytical engine * ChIP-seq analysis pipeline (additional pipelines in development) * Integration of experimental metadata and data files with Galaxy to guide users to choose workflows, parameters, and data sources Stem Cell Commons is based on open source software and is available for download and development.

Proper citation: Stem Cell Commons (RRID:SCR_004415) Copy   

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http://www.ncbi.nlm.nih.gov/biosystems/

Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.

Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy   

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http://www.ebi.ac.uk/

Non-profit academic organization for research and services in bioinformatics. Provides freely available data from life science experiments, performs basic research in computational biology, and offers user training programme, manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures. Part of EMBL.

Proper citation: European Bioinformatics Institute (RRID:SCR_004727) Copy   

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http://www.proconsortium.org/pro/

An ontological representation of protein-related entities by explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. The ontology has a meta-structure encompassing three areas: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp). NOTICE: The PRO ID format has changed from PRO: to PR: (e.g. PRO:000000563 is now PR:000000563).

Proper citation: PR (RRID:SCR_004964) Copy   

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http://www.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

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https://www.rostlab.org/services/snpdbe/

A database to fill the annotation gap left by the high cost of experimental testing for functional significance of protein variants. It joins related bits of knowledge, currently distributed throughout various databases, into a consistent, easily accessible, and updatable resource. It currently covers over 155,000 protein sequences which come from more than 2,600 organisms. Overall more than one million single amino acid substitutions (SAASs) are referenced consisting of natural variants, SAASs from mutagenesis experiments and sequencing conflicts. SNPdbe offers the following pieces of information (if available) on each SAAS: * Experimentally derived functional and structural impact * Predicted functional effect * Associated disease * Average heterozygosity * Experimental evidence of the nsSNP * Evolutionary conservation of wildtype and mutant amino acid * Link-outs to external databases A convenient webinterface to query SAASs on the following levels is offered: * Protein and gene identifiers and keywords * Disease keywords * Protein sequence on different sequence identity thresholds * Variant identifier (dbSNP rs, SwissVar, PMD) or specific mutant like XposY and specified sequence They offer the possibility to submit protein sequences along with experimentally substantiated mutations in order to predict their functional effect and inclusion into our database.

Proper citation: SNPdbe (RRID:SCR_005190) Copy   

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http://www.bioextract.org/GuestLogin

An open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet.

Proper citation: BioExtract (RRID:SCR_005397) Copy   

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http://llama.mshri.on.ca/synergizer/translate/

The Synergizer database is a growing repository of gene and protein identifier synonym relationships. This tool facilitates the conversion of identifiers from one naming scheme (a.k.a namespace) to another. The Synergizer is a service for translating between sets of biological identifiers. It can, for example, translate Ensembl Gene IDs to Entrez Gene IDs, or IPI IDs to HGNC gene symbols, and much more. Unlike some other tools for this purpose, The Synergizer is simple and easy to learn. The Synergizer works via a web interface (for users who are not programmers) or through a web service (for programmatic access).

Proper citation: Synergizer (RRID:SCR_005308) Copy   

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http://users-birc.au.dk/biopv/php/fabox/

Tools for splitting, joining and otherwise manipulating FASTA format sequence files. The first tools in the toolbox is for manipulating fasta headers, cropping alignments and doing some sequence comparison allowing users to combine the description of data (often in excel spreadsheets) with the actual data (often DNA sequences). Also, producing correct input files for a range of programs seems to be problematic for the average user. Hence, some converters in some of the services have been included as well as some stand-alone converters. The converters are not necessarily meant to provide the final input file, but you''ll get a valid input file for Arlequin, MrBayes etc. - that you may further edit so it suit your needs. This means that you may need to combine several of the tools to finish your handling - but it keeps it relatively simple to use. Please note that FaBox is written in PHP and ONLY RUNS ON A WEBSERVER.

Proper citation: FaBox (RRID:SCR_005350) Copy   

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http://www.jcvi.org/cgi-bin/tigrfams/index.cgi

Consists curated multiple sequence alignments, Hidden Markov Models (HMMs) for protein sequence classification, and associated information designed to support automated annotation of (mostly prokaryotic) proteins. Starting with release 10.0, TIGRFAMs models use HMMER3, which provides excellent search speed as well as exquisite search sensitivity. See the "TIGRFAMs Complete Listing" page to review the accession, protein name, model type, and EC number (if assigned) of all models. TIGRFAMs is a member database in InterPro. The HMM libraries and supporting files are available to download and use for free from our FTP site.

Proper citation: TIGRFAMS (RRID:SCR_005493) Copy   

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http://www.ncbi.nlm.nih.gov/gtr/

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/

The Roth Laboratory is designing and interpreting large-scale experiments to understand pathway structure and its relationship to phenotype and human disease. Software for research focused on a specific research goal is available. Current experimental interests: * Exploiting parallel sequencing technology to phenotype all pairwise gene deletion combinations in S. cerevisiae, with initial application to genes involved in transcription. * Generation of S. cerevisiae strains carrying dozens of chosen targeted deletions, with initial application to delete all ABC transporters imparting multidrug resistance. * Targeted insertion of gene sets encoding entire human pathways into S. cerevisiae, with initial application to genes involved in drug metabolism. Current computational interests: * Systematic analysis of genetic interaction to reveal redundant systems and order of action in genetic pathways * Integrating large-scale studies - including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns - to quantitatively assign function to genes and guide experimentation and disease association studies. * Alternative splicing and its relationship to protein interaction networks.

Proper citation: Roth Laboratory (RRID:SCR_005711) Copy   

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http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

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http://www.molgen.de

The research of the group concentrates on the molecular biology of Gram-positive bacteria, with Bacillus subtilis and Lactococcus lactis as the main model organisms. A number of important (human) pathogens are also investigated: Bacillus cereus, Streptococcus pneumoniae and Enterococcus faecalis. The nature of the research is both fundamental and application-oriented. Transcript- and protein profiling by high-throughput technologies such as DNA microarrays and proteomics tools are being used. The very large data sets generated are analyzed by employing existing and novel bioinformatics tools. Major lines of research are in the field of functional genomics of these organisms, using systems- and synthetic biology approaches.

Proper citation: MolGen (RRID:SCR_005700) Copy   

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http://agbase.msstate.edu/cgi-bin/tools/goprofiler_select.pl

Service that provides a summary of GO annotations available for each species. The user provides a taxon id and GOProfiler displays the number of GO associations and the number of annotated proteins for that species. The results are listed by evidence code and a separate list of unannotated proteins is also provided.

Proper citation: GOProfiler (RRID:SCR_005683) Copy   

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http://www.pandora.cs.huji.ac.il/

With PANDORA, you can search for any non-uniform sets of proteins and detect subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA supports GO annotations as well as additional keywords (from UniProt Knowledgebase, InterPro, ENZYME, SCOP etc). It is also integrated into the ProtoNet system, thus allowing testing of thousands of automatically generated protein families. Note that PANDORA replaces the ProtoGO browser developed by the same group. Platform: Online tool

Proper citation: Pandora - Protein ANnotation Diagram ORiented Analysis (RRID:SCR_005686) Copy   

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http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

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http://www.compbio.dundee.ac.uk/downloads/oxbench/

A suite of programs aimed at developers of alignment methods rather than end-users to assess the accuracy of multiple sequence alignment methods. It includes a reference database of protein multiple sequence alignments that were generated by consideration of protein three-dimensional structure.

Proper citation: OXBench (RRID:SCR_005591) Copy   

•   Source: SciCrunch Registry