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http://microbes.ucsc.edu/cgi-bin/hgGateway?db=neisMeni_MC58_1

Portal contains detailed information for Neisseria meningitidis MC58. Information include DNA molecule summary, primary annotation summary, and taxonomy. It is a tool that allows the researcher to access all of the bacterial genome sequences completed to date. Users may access information on all of the bacterial genomes or any subset of them. Information in the website about its DNA molecule includes: total number of DNA molecules, total size of all DNA molecules, number of primary annotation coding bases, and number of G + C bases. Its primary annotation summary include: total genes, protein coding genes, tRNA genes, and rRNA genes. Sponsors: The CMR was previously funded by two grants, one from the U.S. Department of Energy (DOE) and one from the National Science Foundation (NSF). It is currently partially funded by a Microbial Sequence Center (MSC) grant from the National Institute of Allergy and Infectious Diseases (NIAID)

Proper citation: Neisseria meningitidis MC58 Genome Page (RRID:SCR_002200) Copy   

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http://insulatordb.uthsc.edu/

A comprehensive collection of experimentally determined and computationally predicted CCCTC-binding factor (CTCF) binding sites (CTCFBS) from the literature. The database is designed to facilitate the studies on insulators and their roles in demarcating functional genomic domains. The CTCFBS Prediction Tool allows users to scan sequences for the single best match to CTCF position weight matrices. Currently (March 2014), the database contains almost 15 million experimentally determined CTCF binding sites across several species. CTCF binding sites were collected from published papers containing CTCF binding sites identified using ChIPSeq or similar methods, data from the ENCODE project, and a set of approximately 100 manually curated binding sites identified by low-throughput experiments. Users can browse insulator sequence features, function annotations, genomic contexts including histone methylation profiles, flanking gene expression patterns and orthologous regions in other mammalian genomes. Users can also retrieve data by text search, sequence search and genomic range search.

Proper citation: CTCFBSDB (RRID:SCR_002279) Copy   

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

Database of high-throughput genome sequences from large-scale genome sequencing centers, including unfinished and finished sequences. It was created to accommodate a growing need to make unfinished genomic sequence data rapidly available to the scientific community in a coordinated effort among the International Nucleotide Sequence databases, DDBJ, EMBL, and GenBank. Sequences are prepared for submission by using NCBI's software tools Sequin or tbl2asn. Each center has an FTP directory into which new or updated sequence files are placed. Sequence data in this division are available for BLAST homology searches against either the htgs database or the month database, which includes all new submissions for the prior month. Unfinished HTG sequences containing contigs greater than 2 kb are assigned an accession number and deposited in the HTG division. A typical HTG record might consist of all the first-pass sequence data generated from a single cosmid, BAC, YAC, or P1 clone, which together make up more than 2 kb and contain one or more gaps. A single accession number is assigned to this collection of sequences, and each record includes a clear indication of the status (phase 1 or 2) plus a prominent warning that the sequence data are unfinished and may contain errors. The accession number does not change as sequence records are updated; only the most recent version of a HTG record remains in GenBank.

Proper citation: High Throughput Genomic Sequences Division (RRID:SCR_002150) Copy   

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http://www.ark-genomics.org/

Portal for studies of genome structure and genetic variation, gene expression and gene function. Provides services including DNA sequencing of model and non-model genomes using both Next Generation and Sanger sequencing , Gene expression analysis using both microarrays and Next Generation Sequencing, High throughput genotyping of SNP and copy number variants, Data collection and analysis supported in-house high performance computing facilities and expertise, Extensive EST clone collections for a number of animal species, all of commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen, Parentage testing using microsatellites and smaller SNP panels. ARK-Genomics has developed network of researchers whom they support through each stage of their genomics research, from grant application, experimental design and technology selection, performing wet laboratory protocols, through to analysis of data often in conjunction with commercial partners.

Proper citation: ARK-Genomics: Centre for Functional Genomics (RRID:SCR_002214) Copy   

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http://www.genoscope.cns.fr/spip/spip.php?lang=en

French national sequencing center with the following resources: * Sequencing ** Genoscope Projects * Environmental genomics ** Microbial diversity in wastewater ** Metabolic genomics * Bioinformatics ** Atelier for comparative genomics ** Computational Systems Biology ** Servers resources *** GGB for Generic Genome Browser: graphic interface for various databases (sequence, annotation, syntenies...) for a given organism. *** MaGe for Magnifying Microbial Genomes: annotation system for microbial genomes.

Proper citation: Genoscope (RRID:SCR_002172) Copy   

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http://www.ddbj.nig.ac.jp

Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.

Proper citation: DNA DataBank of Japan (DDBJ) (RRID:SCR_002359) Copy   

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

Database that organizes information on genomes including sequences, maps, chromosomes, assemblies, and annotations in six major organism groups: Archaea, Bacteria, Eukaryotes, Viruses, Viroids, and Plasmids. Genomes of over 1,200 organisms can be found in this database, representing both completely sequenced organisms and those for which sequencing is in progress. Users can browse by organism, and view genome maps and protein clusters. Links to other prokaryotic and archaeal genome projects, as well as BLAST tools and access to the rest of the NCBI online resources are available.

Proper citation: NCBI Genome (RRID:SCR_002474) Copy   

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https://cghub.ucsc.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. A secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. CGHub gives scientific researchers the statistical power of large cancer genome datasets to attack the molecular complexity of cancer.

Proper citation: Cancer Genomics Hub (RRID:SCR_002657) Copy   

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http://bioweb.ensam.inra.fr/esther

Database and tools for analysis of protein and nucleic acid sequences belonging to superfamily of alpha/beta hydrolases homologous to cholinesterases. Covers multiple species, including human, mouse caenorhabditis and drosophila., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ESTHER (RRID:SCR_002621) Copy   

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http://www.nitrc.org/projects/penncnv

A free software tool for Copy Number Variation (CNV) detection from SNP genotyping arrays. Currently it can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs form segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.

Proper citation: PennCNV (RRID:SCR_002518) Copy   

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http://genespeed.ccf.org/home/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. Database and customized tools to study the PFAM protein domain content of the transcriptome for all expressed genes of Homo sapiens, Mus musculus, Drosophila melanogaster, and Caenorhabditis elegans tethered to both a genomics array repository database and a range of external information resources. GeneSpeed has merged information from several existing data sets including the Gene Ontology Consortium, InterPro, Pfam, Unigene, as well as micro-array datasets. GeneSpeed is a database of PFAM domain homology contained within Unigene. Because Unigene is a non-redundant dbEST database, this provides a wide encompassing overview of the domain content of the expressed transcriptome. We have structured the GeneSpeed Database to include a rich toolset allowing the investigator to study all domain homology, no matter how remote. As a result, homology cutoff score decisions are determined by the scientist, not by a computer algorithm. This quality is one of the novel defining features of the GeneSpeed database giving the user complete control of database content. In addition to a domain content toolset, GeneSpeed provides an assortment of links to external databases, a unique and manually curated Transcription Factor Classification list, as well as links to our newly evolving GeneSpeed BetaCell Database. GeneSpeed BetaCell is a micro-array depository combined with custom array analysis tools created with an emphasis around the meta analysis of developmental time series micro-array datasets and their significance in pancreatic beta cells.

Proper citation: GeneSpeed- A Database of Unigene Domain Organization (RRID:SCR_002779) 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.gabipd.org/

Database that collects, integrates and links all relevant primary information from the GABI plant genome research projects and makes them accessible via internet. Its purpose is to support plant genome research in Germany, to yield information about commercial important plant genomes, and to establish a scientific network within plant genomic research.
GreenCards is the main interface for text based retrieval of sequence, SNP, mapping data etc. Sharing and interchange of data among collaborating research groups, industry and the patent- and licensing agency are facilitated.
* GreenCards: Text based search for sequence, mapping, SNP data etc. * Maps: Visualization of genetic or physical maps. * BLAST: Secure BLAST search against different public databases or non-public sequence data stored in GabiPD. * Proteomics: View interactive 2D-gels and view or download information for identified protein spots. Registered users can submit data via secure file upload.

Proper citation: Gabi Primary Database (RRID:SCR_002755) Copy   

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http://www.genomesonline.org/

Database of information regarding genome and metagenome sequencing projects, and their associated metadata, around the world. It also provides information related to organism properties such as phenotype, ecotype and disease. Both complete and ongoing projects, along with their associated metadata, can be accessed. Users can also register, annotate and publish genome and metagenome data.

Proper citation: Genomes Online Database (RRID:SCR_002817) Copy   

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https://www.hgsc.bcm.edu/content/sea-urchin-genome-project

The genome of the California Purple Sea Urchin (Strongylocentrotus purpuratus) has been sequenced and annotated by the Sea Urchin Genome Sequencing Consortium led by the HGSC. Currently, the echinoderms Strongylocentrotus franciscanus and Allocentrotus fragilis (fragile urchin) are being sequenced for comparative analysis. The sea urchin has been an important model system for studying modern molecular, evolutionary and cell biology particularly in the realm of developmental biology. Echinoderms occupy an important evolutionary position with respect to vertebrates and humans: they, along with their sister phylum hemichordates, are the closest known relatives to chordates. The sea urchin was sequenced using the Clone-Array Pooled Shotgun Sequencing (CAPSS) method where shotgun libraries are made from row and column pools of arrayed BACs from an FPC generated tiling path (BC Genome Sciences Center). The deconvoluted individual BAC sequences as well as assemblies enriched with WGS sequences from the BAC region are available in GenBank. Sponsors: This project is funded by the National Human Genome Research Institute (NHGRI), National Institutes of Health. The white paper describing this project was developed by Eric Davidson and Andrew Cameron at California Institute of Technology in collaboration with the sea urchin genome advisory group and the HGSC.

Proper citation: Sea Urchin Genome Project (RRID:SCR_002841) Copy   

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http://www.greenphyl.org/

A database designed for plant comparative and functional genomics based on complete genomes. It comprises complete proteome sequences from the major phylum of plant evolution. The clustering of these proteomes was performed to define a consistent and extensive set of homeomorphic plant families. Based on this, lists of gene families such as plant or species specific families and several tools are provided to facilitate comparative genomics within plant genomes. The analyses follow two main steps: gene family clustering and phylogenomic analysis of the generated families. Once a group of sequences (cluster) is validated, phylogenetic analyses are performed to predict homolog relationships such as orthologs and ultraparalogs.

Proper citation: GreenPhylDB (RRID:SCR_002834) Copy   

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http://www.ambystoma.org/

Portal that supports Ambystoma-related research and educational efforts. It is composed of several resources: Salamander Genome Project, Ambystoma EST Database, Ambystoma Gene Collection, Ambystoma Map and Marker Collection, Ambystoma Genetic Stock Center, and Ambystoma Research Coordination Network.

Proper citation: Sal-Site (RRID:SCR_002850) Copy   

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http://cbio.mskcc.org/

Computational biology research at Memorial Sloan-Kettering Cancer Center (MSKCC) pursues computational biology research projects and the development of bioinformatics resources in the areas of: sequence-structure analysis; gene regulation; molecular pathways and networks, and diagnostic and prognostic indicators. The mission of cBio is to move the theoretical methods and genome-scale data resources of computational biology into everyday laboratory practice and use, and is reflected in the organization of cBio into research and service components ~ the intention being that new computational methods created through the process of scientific inquiry should be generalized and supported as open-source and shared community resources. Faculty from cBio participate in graduate training provided through the following graduate programs: * Gerstner Sloan-Kettering Graduate School of Biomedical Sciences * Graduate Training Program in Computational Biology and Medicine Integral to much of the research and service work performed by cBio is the creation and use of software tools and data resources. The tools that we have created and utilize provide evidence of our involvement in the following areas: * Cancer Genomics * Data Repositories * iPhone & iPod Touch * microRNAs * Pathways * Protein Function * Text Analysis * Transcription Profiling

Proper citation: Computational Biology Center (RRID:SCR_002877) Copy   

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http://locus.jouy.inra.fr/cgi-bin/lgbc/mapping/common/intro2.pl?BASE=goat

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This website contains information about the mapping of the caprine genome. It contains loci list, phenes list, cartography, gene list, and other sequence information about goats. This website contains 731 loci, 271 genes, and 1909 homologue loci on 112 species. It also allows users to summit their own data for Goatmap. ARK-Genomics is not-for-profit and has collaborators from all over the world with an interest in farm animal genomics and genetics. ARK-Genomics was initially set up in 2000 with a grant awarded from the BBSRC IGF (Investigating Gene Function) initiative and from core resources of the Roslin Institute to provide a laboratory for automated analysis of gene expression using state-of-the-art genomic facilities. Since then, ARK-Genomics has expanded considerably, building up considerable expertise and resources.

Proper citation: GoatMap Database (RRID:SCR_008144) Copy   

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http://genome.wustl.edu/projects/detail/human-gut-microbiome/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2022. Human Gut Microbiome Initiative (HGMI) seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota. Humans are supra-organisms, composed of 10 times more microbial cells than human cells. Therefore, it seems appropriate to consider ourselves as a composite of many species - human, bacterial, and archaeal - and our genome as an amalgamation of human genes and the genes in ''our'' microbial genomes (''microbiome''). In the same sense, our metabolome can be considered to be a synthesis of co-evolved human and microbial traits. The total number of genes present in the human microbiome likely exceeds the number of our H. sapiens genes by orders of magnitude. Thus, without an understanding of our microbiota and microbiome, it not possible to obtain a complete picture of our genetic diversity and of our normal physiology. Our intestine is home to our largest collections of microbes: bacterial densities in the colon (up to 1 trillion cells/ml of luminal contents) are the highest recorded for any known ecosystem. The vast majority of phylogenetic types in the distal gut microbiota belong to just two divisions (phyla) of the domain Bacteria - the Bacteroidetes and the Firmicutes. Members of eight other divisions have also been identified using culture-independent 16S rRNA gene-based surveys. Metagenomic studies of complex microbial communities residing in our various body habitats are limited by the availability of suitable reference genomes for confident assignment of short sequence reads generated by highly parallel DNA sequencers, and by knowledge of the professions (niches) of community members. Therefore, HGMI, which represents a collaboration between Washington University''s Genome Center and its Center for Genome Sciences, seeks to provide simply annotated, deep draft genome sequences for 100 cultured representatives of the phylogenetic diversity documented by 16S rRNA surveys of the human gut microbiota.

Proper citation: Human Gut Microbiome Initiative (RRID:SCR_008137) Copy   

•   Source: SciCrunch Registry