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http://go.princeton.edu/cgi-bin/GOTermFinder

The Generic GO Term Finder finds the significant GO terms shared among a list of genes from an organism, displaying the results in a table and as a graph (showing the terms and their ancestry). The user may optionally provide background information or a custom gene association file or filter evidence codes. This tool is capable of batch processing multiple queries at once. GO::TermFinder comprises a set of object-oriented Perl modules GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script. This implementation, developed at the Lewis-Sigler Institute at Princeton, depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University and the GO:View module written by Shuai Weng. It is made publicly available through the GMOD project. The full source code and documentation for GO:TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Generic GO Term Finder (RRID:SCR_008870) Copy   

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http://hymenopteragenome.org/beebase/

Gene sequences and genomes of Bombus terrestris, Bombus impatiens, Apis mellifera and three of its pathogens, that are discoverable and analyzed via genome browsers, blast search, and apollo annotation tool. The genomes of two additional species, Apis dorsata and A. florea are currently under analysis and will soon be incorporated.BeeBase is an archive and will not be updated. The most up-to-date bee genome data is now available through the navigation bar on the HGD Home page.

Proper citation: BeeBase (RRID:SCR_008966) 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://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

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http://weblogo.berkeley.edu

Web application to generate sequence logos, graphical representations of patterns within multiple sequence alignment. Designed to make generation of sequence logos easy. Sequence logo generator.

Proper citation: WEBLOGO (RRID:SCR_010236) Copy   

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http://www.bcgsc.ca/platform/bioinfo/software/abyss

Software providing de novo, parallel, paired-end sequence assembler that is designed for short reads. ABySS 1.0 originally showed that assembling human genome using short 50 bp sequencing reads was possible by aggregating half terabyte of compute memory needed over several computers using standardized message passing system. ABySS 2.0 is Resource Efficient Assembly of Large Genomes using Bloom Filter. ABySS 2.0 departs from MPI and instead implements algorithms that employ Bloom filter, probabilistic data structure, to represent de Bruijn graph and reduce memory requirements.

Proper citation: ABySS (RRID:SCR_010709) Copy   

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http://uberon.org

An integrated cross-species anatomy ontology representing a variety of entities classified according to traditional anatomical criteria such as structure, function and developmental lineage. The ontology includes comprehensive relationships to taxon-specific anatomical ontologies, allowing integration of functional, phenotype and expression data. Uberon consists of over 10000 classes (March 2014) representing structures that are shared across a variety of metazoans. The majority of these classes are chordate specific, and there is large bias towards model organisms and human.

Proper citation: UBERON (RRID:SCR_010668) Copy   

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http://compbio.med.harvard.edu/antibodies/

The aim of this site is to collect and to share experimental results on antibodies that would otherwise remain in laboratories, thus aiding researchers in selection and validation of antibodies.

Proper citation: Antibody Validation Database (RRID:SCR_011996) Copy   

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

Catalog of published genome-wide association studies. Genome-wide set of genetic variants in different individuals to see if any variant is associated with trait and disease. Database of genome-wide association study (GWAS) publications including only those attempting to assay single nucleotide polymorphisms (SNPs). Publications are organized from most to least recent date of publication. Studies are identified through weekly PubMed literature searches, daily NIH-distributed compilations of news and media reports, and occasional comparisons with an existing database of GWAS literature (HuGE Navigator). Works with HANCESTRO ancestry representation.

Proper citation: GWAS: Catalog of Published Genome-Wide Association Studies (RRID:SCR_012745) Copy   

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Ratings or validation data are available for this resource

http://ccb.jhu.edu/software/tophat/index.shtml

Software tool for fast and high throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies. Fast splice junction mapper for RNA-Seq reads. Aligns RNA-Seq reads to mammalian-sized genomes using ultra high-throughput short read aligner Bowtie, and then analyzes mapping results to identify splice junctions between exons.TopHat2 is accurate alignment of transcriptomes in presence of insertions, deletions and gene fusions.

Proper citation: TopHat (RRID:SCR_013035) Copy   

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http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

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http://www.crossmodel.org/

An international consortium whose goals are to enable faster comparative studies and develop tools that make analysis accessible to the wider scientific community. InterMOD is an open source data warehouse where users can query and input their own data, access analysis tools, and create their own InterMine. Five core mines make make up InterMOD: RGD, SGD ZFIN, MGI, and WormBase.

Proper citation: InterMOD (RRID:SCR_013808) Copy   

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https://bioconductor.org/packages/release/bioc/html/oligo.html

Software package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

Proper citation: oligo (RRID:SCR_015729) Copy   

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https://www.encodeproject.org/

Consortium to build comprehensive parts list of functional elements in human genome. This includes elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Data from 2012-present.

Proper citation: Encode (RRID:SCR_015482) Copy   

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http://www.biostars.org/

A question answer forum for scientists, focusing on methods in bioinformatics, computational genomics and biological data analysis. They welcome detailed and specific posts, written clearly and simply.

Proper citation: BioStar (RRID:SCR_002580) Copy   

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http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

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http://www.cbil.upenn.edu/RAD

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.

Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy   

•   Source: SciCrunch Registry

http://diseasome.eu

A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems.

Proper citation: Diseasome (RRID:SCR_002792) Copy   

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http://www.flymine.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 14,2026. Integrated database of genomic, expression and protein data for Drosophila, Anopheles, C. elegans and other organisms. You can run flexible queries, export results and analyze lists of data. FlyMine presents data in categories, with each providing information on a particular type of data (for example Gene Expression or Protein Interactions). Template queries, as well as the QueryBuilder itself, allow you to perform searches that span data from more than one category. Advanced users can use a flexible query interface to construct their own data mining queries across the multiple integrated data sources, to modify existing template queries or to create your own template queries. Access our FlyMine data via our Application Programming Interface (API). We provide client libraries in the following languages: Perl, Python, Ruby and & Java API

Proper citation: FlyMine (RRID:SCR_002694) Copy   

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http://www.ncbi.nlm.nih.gov/lovd/home.php?select_db=OCRL

The Lowe Syndrome Mutation Database is now being maintained by the National Center for Biotechnology Information (NCBI) at the National Institutes of Health. A database of mutations causing Lowe syndrome. Information on new mutations may be submitted online. Lowe oculocerebrorenal syndrome is an X-linked disorder caused by mutations in the OCRL1 gene, which encodes a 105-kDa Golgi protein with phosphatidylinositol (4,5) bisphosphate 5-phosphatase activity. genetics

Proper citation: Lowes Syndrome Mutation Database (RRID:SCR_002907) Copy   

•   Source: SciCrunch Registry