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https://fgr.hms.harvard.edu/

Database that provides free online tools to users to allow the retrieval of information related to the Drosophila genome and allows access to genome-wide and related cell-based screening of Drosophila at Harvard Medical School (for a fee) . Tools available include SnapDragon, and RNAi designer, a heat map tool for viewing screen data, and gene and amplicon search and download tools. The DRSC mainly exists to provide Drosophila genome screening services, including help with assay development and optimization, data and image analysis, and planning of follow-up assays.

Proper citation: Drosophila RNAi Screening Center (RRID:SCR_000733) Copy   

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http://www-abcdb.biotoul.fr

ABCdb is a public resource devoted to the ATP-binding Cassette (ABC) transporters encoded by completely sequenced prokaryotic genomes. In order to establish, in a complete genome, the repertory of ABC systems, we have to: i) identify the different partners, ii) assemble the partners in putative systems, and iii) classify the system into the correct functional subfamily (Quentin et al., 2002). The main pitfalls were the identification of loosely conserved domains and the assembly of partners encoded by genes dispersed over the chromosome. In order to face the avalanche of newly sequenced genomes, we decided to also feed into the database the raw prediction issued by this automatic procedure, before time consuming review by an expert occurs. Therefore, the database comprises two sections: CleanDb, for data checked by an expert and AutoDb for raw data. The ABC proteins are involved in a wide variety of physiological processes in Archaea, Bacteria and Eucaryota where they are encoded by large families of paralogous genes. The majority of ABC domains energize the transport of compounds across membranes. In bacteria, ABC transporters are involved in the uptake of a wide variety of molecules, as well as in mechanisms of virulence and antibiotic resistance. In eukaryotes, most of them are involved in drug resistance and in human cell, many are associated with diseases. Sequence analysis reveals that members of the ABC superfamily can be organized into sub-families, and suggests that they have diverged from common ancestral forms. A typical ABC transporter system is composed of an assembly of protein domains that serve different functions: i) two Nucleotide Binding Domains (NBD) that energize transport via ATP hydrolysis, ii) two Membrane Spanning Domains (MSD) that act as a membrane channel for the substrate, and iii) for the importer, a Solute Binding Protein (SBP) that confers substrates specificity on the transporter. The different partners of an ABC system are generally encoded by neighboring genes. The database includes information on: * ABC transporters * Protein partners * Protein domains (NBD, MSD and SBP) * Classification of ABC transporters and their protein partners * Taxonomy of the species Each model Protein includes a link to the Peptide sequence, general information extracted from EMBL files, and specific tags to store results of predictions. The results of the annotation procedure are reachable through the class Prediction. The origin of the proteins is modeled as a path through the classes Chromosome, Strain, Species, and Taxon. Assembly and protein compilation tables are also provided for each of the chromosomes ( Assembly and Protein ).

Proper citation: Archaeal and Bacterial ABC Transporter Database (RRID:SCR_001692) Copy   

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2039752/

It aims to help researchers to utilize information more efficiently from the published association data. This database is freely accessible only for academic users under the GNU GPL PADB indexes the sentences containing "associat*" or "case-control*" or "cohort*" or "meta-analysis" or "systematic review" or "odds ratio*" or "hazard ratio*" or "risk ratio*" or "relative risk*" from PubMed abstracts and automatically extracts the numeric values of odds ratios, hazard ratios, risk ratios and relative risks data when available. PADB automatically identifies HUGO official symbols of human genes using NCBI Entrez Gene data, and each gene is linked to the UCSC genome browser and International HapMap Project database. Furthermore, molecular pathways listed in BioCarta or KEGG databases can be accessed through the link using CGAP gene annotation data. Also, each record in PADB is linked to GAD or HPLD if it is available from those databases. Currently, (Last Update of Database Contents : Dec. 20, 2006) PADB indexes more than 1,500,000 abstracts including about 190,000 risk values ranging from 0.00001 to 4878.9 and 3,442 human genes related to 461 molecular pathways. Sponsors: This work was supported by the Brain Korea 21 Project for Medical Science, Yonsei University, Seoul, Korea and a faculty research grant of Yonsei University College of Medicine for 2006, Seoul, Korea.

Proper citation: Published Association Database (RRID:SCR_001841) Copy   

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https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

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http://mus.well.ox.ac.uk/gscandb/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.

Proper citation: WTCHG Genome Scan Viewer (RRID:SCR_001635) Copy   

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http://hertellab.mmg.uci.edu/cgi-bin/HEXEvent/HEXEventWEB.cgi

A free database that provides a list of human internal exons and reports all their known splice events based on EST information from the UCSC Genome Browser. This list can be restricted by the user to either only a specific region in the genome (by specifying the chromosome, the strand and the start and end position), to a whole chromosome or to a group of genes. Furthermore, exons can be filtered according to their splicing type (constitutive exons, cassette exons and exons with one or more alternative 3' and/or 5' splice sites). In order to extract a customized set of exons, the user-specific definitions of exon types can be fixed. The user needs to specify in what fraction of ESTs an exon is allowed to be alternatively spliced in order to still be called constitutive. Furthermore, the user can restrict the set of requested cassette exons by a certain upper inclusion level, which, for instance, is useful when only looking for low-inclusion exons.

Proper citation: HEXEvent (RRID:SCR_002106) Copy   

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http://www.bacteriome.org

Database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase. Presently the resource offers access to two types of network: * A network of functional interactions derived through exploiting available functional genomic datasets within a Bayesian framework * Two networks of experimentally derived protein-protein interactions - a "core" network consisting of interactions deemed to be of "high quality"; and an "extended" network which extends the "core" network by including interactions for which experimental evidence is less strong.

Proper citation: Bacteriome.org (RRID:SCR_001934) Copy   

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http://beetlebase.org/

A centralized sequence database and community resource for Tribolium genetics, genomics and developmental biology containing genomic sequence scaffolds mapped to 10 linkage groups, genetic linkage maps, the official gene set, Reference Sequences from NCBI (RefSeq), predicted gene models, ESTs and whole-genome tiling array data representing several developmental stages. The current version of Beetlebase is built on the Tribolium castaneum 3.0 Assembly (Tcas 3.0) released by the Human Genome Sequencing Center at the Baylor College of Medicine. The database is constructed using the upgraded Generic Model Organism Database (GMOD) modules. The genomic data is stored in a PostgreSQL relational database using the Chado schema and visualized as tracks in GBrowse. The genetic map is visualized using the comparative genetic map viewer CMAP. To enhance search capabilities, the BLAST search tool has been integrated with the GMOD tools. Tribolium castaneum is a very sophisticated genetic model organism among higher eukaryotes. As the member of a primitive order of holometabolous insects, Coleoptera, Tribolium is in a key phylogenetic position to understand the genetic innovations that accompanied the evolution of higher forms with more complex development. Coleoptera is also the largest and most species diverse of all eukaryotic orders and Tribolium offers the only genetic model for the profusion of medically and economically important species therein. The genome sequences may be downloaded.

Proper citation: BeetleBase (RRID:SCR_001955) Copy   

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http://genome.jgi.doe.gov/programs/fungi/index.jsf

Fungal genomics database and interactive analytical tools that integrates all fungal genomes for diverse fungi that are important for energy and environment, the focus of the JGI Fungal program. It integrates genomics data from the DOE JGI and its users and promotes user community participation in data submission, annotation and analysis. Over 100 newly sequenced and annotated fungal genomes from JGI and elsewhere are available to the public through MycoCosm, and new annotated genomes are being added to this resource upon completion of annotation. MycoCosm offers web-based genome analysis tools for fungal biologists to ''navigate'' through sequenced genomes and explore them in the context of ''genome-centric'' and ''comparative views''.

Proper citation: MycoCosm (RRID:SCR_005312) Copy   

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http://www.uib.no/en/cbu

An inter-department center that conducts bioinformatics research and expands the interface between bioinformatics and experimental biological and biomedical research. The unit is closely associated with the the Bioinformatics group at the Department of Informatics (II) and has tight links with the Sars Centre for Marine Molecular biology (SARS) and the Department of Molecular Biology (MBI). Six research groups are currently associated with CBU with projects that include sequence and structure analysis, molecular evolution, genome annotation and genomics data analysis. CBU also provides services and contributes to bioinformatics education primarily through training courses.

Proper citation: University of Bergen Computational Biology Unit (RRID:SCR_002970) Copy   

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http://blocks.fhcrc.org/blocks/codehop.html

This COnsensus-DEgenerate Hybrid Oligonucleotide Primer (CODEHOP) strategy has been implemented as a computer program that is accessible over the World-Wide Web and is directly linked from the BlockMaker multiple sequence alignment site for hybrid primer prediction beginning with a set of related protein sequences. This is a new primer design strategy for PCR amplification of unknown targets that are related to multiply-aligned protein sequences. Each primer consists of a short 3' degenerate core region and a longer 5' consensus clamp region. Only 3-4 highly conserved amino acid residues are necessary for design of the core, which is stabilized by the clamp during annealing to template molecules. During later rounds of amplification, the non-degenerate clamp permits stable annealing to product molecules. The researchers demonstrate the practical utility of this hybrid primer method by detection of diverse reverse transcriptase-like genes in a human genome, and by detection of C5 DNA methyltransferase homologs in various plant DNAs. In each case, amplified products were sufficiently pure to be cloned without gel fractionation. Sponsors: This work was supported in part by a grant from the M. J. Murdock Charitable Trust and by a grant from NIH. S. P. is a Howard Hughes Medical Institute Fellow of the Life Sciences Research Foundation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 15,2026.

Proper citation: COnsensus-DEgenerate Hybride Oligonucleotide Primers (RRID:SCR_002875) Copy   

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http://www.cazy.org

Database that describes the families of structurally-related catalytic and carbohydrate-binding modules (or functional domains) of enzymes that degrade, modify, or create glycosidic bonds. This specialist database is dedicated to the display and analysis of genomic, structural and biochemical information on Carbohydrate-Active Enzymes (CAZymes). CAZy data are accessible either by browsing sequence-based families or by browsing the content of genomes in carbohydrate-active enzymes. New genomes are added regularly shortly after they appear in the daily releases of GenBank. New families are created based on published evidence for the activity of at least one member of the family and all families are regularly updated, both in content and in description. An original aspect of the CAZy database is its attempt to cover all carbohydrate-active enzymes across organisms and across subfields of glycosciences. One can search for CAZY Family pages using the Protein Accession (Genpept Accession, Uniprot Accession or PDB ID), Cazy family name or EC number. In addition, genomes can be searched using the NCBI TaxID. This search can be complemented by Google-based searches on the CAZy site.

Proper citation: CAZy- Carbohydrate Active Enzyme (RRID:SCR_012909) Copy   

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http://www.plantagora.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. A web-based plant genome assembly simulation platform whose resources include out of the box scripts for analyzing assembly data, an on-demand web graphing tool to model your experiment, and a downloadable database with metrics and parameters from over 3,000 simulated genome assemblies.

Proper citation: Plantagora (RRID:SCR_001227) Copy   

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https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   

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http://deepbase.sysu.edu.cn/chipbase/

A database for decoding transcription factor binding maps, expression profiles and transcriptional regulation of long non-coding RNAs (lncRNAs, lincRNAs), microRNAs, other ncRNAs (snoRNAs, tRNAs, snRNAs, etc.) and protein-coding genes from ChIP-Seq data. ChIPBase currently includes millions of transcription factor binding sites (TFBSs) among 6 species. ChIPBase provides several web-based tools and browsers to explore TF-lncRNA, TF-miRNA, TF-mRNA, TF-ncRNA and TF-miRNA-mRNA regulatory networks., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ChIPBase (RRID:SCR_005404) Copy   

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http://genome.jgi.doe.gov/programs/plants/index.jsf

The goal of the DOE JGI Plant Genome Program is to shed light on the fundamental biology of photosynthesis and transduction of solar to chemical energy. Other areas of interest include characterizing: * Ecosystems and the role of terrestrial plants and oceanic phytoplankton-in carbon sequestration. * The role of plants in coping with toxic pollutants in soils by hyper-accumulation and detoxification. * Feedstocks for biofuels, e.g., biodiesel from soybean; cellulosic ethanol from perennial grasses. * The ability to respond to environmental change (e.g., loss of diversity from monoculture produces vulnerabilities; nitrogen fixing nodules in legumes reduce fertilizer need). * The generation of useful secondary metabolites (produced largely for disease resistance)- for positive/negative control in agriculture, with attendant influence on global carbon cycle. The Plant Genome Program accomplishes the above through the following activities: # Sequence. Produce genome sequences of key plant (and algal) species to accelerate biofuel development and understand response to climate change. # Function. Develop datasets (and synthetic biology tools) to elucidate functional elements in plant genomes, with special focus on handful of flagship genomes. # Variation. Characterize natural genomic variation in plants (and their associated microbiomes), and relate to biofuel sustainability and adaptation to climate change. # Integration. Provide a centralized hub for the retrieval and deep integrated analysis of plant genome datasets.

Proper citation: Plant Genome Resource at JGI (RRID:SCR_005315) Copy   

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http://avia.abcc.ncifcrf.gov/apps/site/index

An interactive web-based tool to explore and interpret large sets of genomic variations (single nucleotide variations and insertion/deletions) to help guide and summarize genomic experiments. The tool is based on coupling a comprehensive annotation pipeline with a flexible visualization method. They leveraged the ANNOVAR (Wang et. al, 2010) framework for assigning functional impact to genomic variations by extending its list of reference annotation databases (RefSeq, UCSC, SIFT, Polyphen etc.) with additional in-house developed sources (Non-B DB, PolyBrowse). Further, because many users also have their own annotation sources, they have added the ability to supply their own files as well. The results can be obtained in tabular format or as tracks in whole genome circular views generated by the Circos application (Krzywinski et. al, 2009). Users can also select different sets of pre-computed tracks, including whole genome distributions of different genomic features (genes, exons, repeats), as well as variations analysis tracks for the 69 CGI public genomes for reference.

Proper citation: AVIA (RRID:SCR_005172) Copy   

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http://www.broadinstitute.org/cancer/cga/oncotator

A tool for annotating human genomic point mutations and indels with data relevant to cancer researchers. Genomic Annotations, Protein Annotations, and Cancer Annotations are aggregated from many resources. A standalone version of Oncotator is being developed.

Proper citation: Oncotator (RRID:SCR_005183) Copy   

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http://wego.genomics.org.cn/cgi-bin/wego/index.pl

Web Gene Ontology Annotation Plot (WEGO) is a simple but useful tool for plotting Gene Ontology (GO) annotation results. Different from other commercial software for chart creating, WEGO is designed to deal with the directed acyclic graph (DAG) structure of GO to facilitate histogram creation of GO annotation results. WEGO has been widely used in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the useful tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. Platform: Online tool

Proper citation: WEGO - Web Gene Ontology Annotation Plot (RRID:SCR_005827) Copy   

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http://rulai.cshl.edu/tred

Collects mammalian cis- and trans-regulatory elements together with experimental evidence. Regulatory elements were mapped on to assembled genomes. Resource for gene regulation and function studies. Users can retrieve primers, search TF target genes, retrieve TF motifs, search Gene Regulatory Networks and orthologs, and make use of sequence analysis tools. Uses databases such as Genbank, EPD and DBTSS, and employ promoter finding program FirstEF combined with mRNA/EST information and cross-species comparisons. Manually curated.

Proper citation: Transcriptional Regulatory Element Database (RRID:SCR_005661) Copy   

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