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http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

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http://www.homd.org/index.php

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on April 14,2022. Database of comprehensive information on the approximately 600 prokaryote species that are present in the human oral cavity. The majority of these species are uncultivated and unnamed, recognized primarily by their 16S rRNA sequences. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference entity. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Full and partial oral bacterial genome sequences determined as part of this project and the Human Microbiome Project, are being added to the HOMD as they become available. HOMD offers easy to use tools for viewing all publicly available oral bacterial genomes. Data is also downloadable.

Proper citation: HOMD (RRID:SCR_012770) Copy   

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http://protists.ensembl.org

The Ensembl Genomes project produces genome databases for important species from across the taxonomic range, using the Ensembl software system. Five sites are now available, one of which is Ensembl Protists, which houses protists species. Sponsors: EnsembProtists is a project run by EMBL - EBI to maintain annotation on selected genomes, based on the software developed in the Ensembl project developed jointly by the EBI and the Wellcome Trust Sanger Institute.

Proper citation: Ensembl Protists (RRID:SCR_013154) Copy   

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http://giardiadb.org

GiardiaDB is a resource for information on Giardia lamblia. It contains gene information, including genomic attributes, protein expression patterns, evolution, and EST sequence information. The website provides tools for BLASTing, sequence retrieval, graphic visualization, and PubMed information.

Proper citation: GiardiaDB (RRID:SCR_013377) Copy   

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http://epsf.bmad.bii.a-star.edu.sg/cube/db/html/home.html

Cube-DB is a database of pre-evaluated conservation and specialization scores for residues in paralogous proteins belonging to multi-member families of human proteins. Protein family classification follows (largely) the classification suggested by HUGO Gene Nomenclature Committee. Sets of orhtologous protein sequences were generated by mutual-best-hit strategy using full vertebrate genomes available in Ensembl. The scores, described on documentation page, are assigned to each individual residue in a protein, and presented in the form of a table (html or downloadable xls formats) and mapped, when appropriate, onto the related structure (Jmol, Pymol, Chimera).

Proper citation: Cube-DB (RRID:SCR_013233) Copy   

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http://planteome.org

An international collaborative effort to develop and enrich new and existing reference ontologies for plants, improve ontology use and cross-references, and to develop data annotation standards. Users can search for ontology terms and bioentities and submit the ontology-related term requests by visiting the following GitHub request trackers.

Proper citation: Planteome (RRID:SCR_014411) Copy   

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http://signal.salk.edu/cgi-bin/RiceGE

Gene database for Japonica rice. RiceGE is associated with SIGnAL at the Salk Institute.

Proper citation: RiceGE (RRID:SCR_015061) Copy   

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http://hb.flatironinstitute.org/

Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.

Proper citation: HumanBase (RRID:SCR_016145) Copy   

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http://gnomad.broadinstitute.org/

Database that aggregates exome and genome sequencing data from large-scale sequencing projects. The gnomAD data set contains individuals sequenced using multiple exome capture methods and sequencing chemistries. Raw data from the projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects.

Proper citation: Genome Aggregation Database (RRID:SCR_014964) Copy   

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http://software.broadinstitute.org/gsea/msigdb/index.jsp

Collection of annotated gene sets for use with Gene Set Enrichment Analysis (GSEA) software.

Proper citation: Molecular Signatures Database (RRID:SCR_016863) Copy   

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https://github.com/adigenova/fast-sg

Algorithm for alignment-free scaffolding graph construction from short or long reads. It allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines.

Proper citation: Fast-SG (RRID:SCR_015934) Copy   

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http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

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http://www.broad.mit.edu/node/305

The Connectivity Map aims to generate a detailed map that links gene patterns associated with disease to corresponding patterns produced by drug candidates and a variety of genetic manipulations. The Connectivity Map is the most comprehensive effort yet for using genomics in a drug-discovery framework. It allows researchers to screen compounds against genome-wide disease signatures, rather than a pre-selected set of target genes. Drugs are paired with diseases using sophisticated pattern-matching methods with a high level of resolution and specificity. To build a Connectivity Map, the Broad Institute brings together molecular biologists, genomics specialists, computational scientists, pharmacologists, chemists and chemical biologists, as well as expertise from across the breadth and depth of medicine.Connectivity map is a large public database of signatures of drugs and genes, and pattern-matching tools to detect similarities among these signatures.The parent site for the Broad Institute at MIT has a software library of software applications developed for use in genetic analysis.

Proper citation: National Institute of Mental Health (NIMH) Human Genetics Initiative (RRID:SCR_007436) Copy   

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http://www.geisha.arizona.edu/geisha/

Online repository for chicken in situ hybridization information. This site presents whole mount in situ hybridization images and corresponding probe and genomic information for genes expressed in chicken embryos in Hamburger Hamilton stages 1-25 (0.5-5 days). The GEISHA project began in 1998 to investigate using high throughput whole mount in situ hybridization to identify novel, differentially expressed genes in chicken embryos. An initial expression screen of approximately 900 genes demonstrated feasibility of the approach, and also highlighted the need for a centralized repository of in situ hybridization expression data. Objectives: The goals of the GEISHA project are to obtain whole mount in situ hybridization expression information for all differentially expressed genes in the chicken embryo between HH stages 1-25, to integrate expression data with the chicken genome browsers, and to offer this information through a user-friendly graphical user interface. In situ hybridization images are obtained from three sources: 1. In house high throughput in situ hybridization screening: cDNAs obtained from several embryonic cDNA libraries or from EST repositories are screened for expression using high throughput in situ hybridization approaches. 2. Literature curation: Agreements with journals permit posting of published in situ hybridization images and related information on the GEISHA site. 3. Unpublished in situ hybridization information from other laboratories: laboratories generally publish only a small fraction of their in situ hybridization data. High quality images for which probe identity can be verified are welcome additions to GEISHA.

Proper citation: GEISHA - Gallus Expression in Situ Hybridization Analysis: A Chicken Embryo Gene Expression Database (RRID:SCR_007440) Copy   

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http://www.genomesize.com

Comprehensive catalogue of animal genome size data. Haploid DNA contents (C-values, in picograms) are available for 4972 species (3231 vertebrates and 1741 non-vertebrates) based on 6518 records from 669 published sources. Data may be submitted directly to the database or reprints and notifications of new papers may be sent to database curation staff.

Proper citation: Animal Genome Size Database (RRID:SCR_007551) Copy   

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http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

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http://genomics.senescence.info/

Collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses. A major resource in HAGR is GenAge, which includes a curated database of genes related to human aging and a database of ageing- and longevity-associated genes in model organisms. Another major database in HAGR is AnAge. Featuring over 4,000 species, AnAge provides a compilation of data on aging, longevity, and life history that is ideal for the comparative biology of aging. GenDR is a database of genes associated with dietary restriction based on genetic manipulation experiments and gene expression profiling. Other projects include evolutionary studies, genome sequencing, cancer genomics, and gene expression analyses. The latter allowed them to identify a set of genes commonly altered during mammalian aging which represents a conserved molecular signature of aging. Software, namely in the form of scripts for Perl and SPSS, is made available for users to perform a variety of bioinformatic analyses potentially relevant for studying aging. The Perl toolkit, entitled the Ageing Research Computational Tools (ARCT), provides modules for parsing files, data-mining, searching and downloading data from the Internet, etc. Also available is an SPSS script that can be used to determine the demographic rate of aging for a given population. An extensive list of links regarding computational biology, genomics, gerontology, and comparative biology is also available.

Proper citation: Human Ageing Genomic Resources (RRID:SCR_007700) Copy   

•   Source: SciCrunch Registry

http://www.projects.roslin.ac.uk/cdiv/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. The objective of the project is the standardization of micro-satellite markers used within participating laboratories, use of DNA markers to define genetic diversity and to enable monitoring of breeds to promote conservation programs where required, and the determination of diversity present in rare and local breeds across Europe. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project (See BovMaP). Work with micro-satellite markers has shown that they are valuable tools for examining genetic diversity and phylogeny in many species. However, for work carried out in different laboratories to be comparable, it is essential that the same markers are used. To maintain the compatibility of data generated by the various typing labs, it is essential that all laboratories adopt the same markers and typing protocols. It is therefore of paramount importance that the blood typing laboratories and research labs that are examining the genetic structure of the cattle populations adopt a common panel of the best micro-satellite markers available. Some pilot comparative work has been undertaken through the International Society for Animal Genetics, but so far this has only involved the blood typing laboratories. One objective of this project is to facilitate the comparison of the micro-satellite markers currently in use in the different types of laboratory and determine the efficiency of the markers available in revealing genetic differences within and among breeds. It will also be important to compare the use of markers in different laboratories to determine how robust they are and how easily results can be compared. From comparison of the markers, those that are most suitable will be selected to form a panel which will be recommended for pedigree validation and genetic surveys. Cattle are an important source of food in Europe, and intense selection has resulted in the development of specialized breeds. Selection for high-producing dairy cattle has been successful, but one associated drawback is that the cattle population, both in Europe and North America, has been skewed dramatically towards one breed, the Holstein/Friesian. So there has been a decline in the number of individuals of other breeds, and hence a general erosion of the genetic base of the cattle population. The progressive move towards the North American-type Holstein animals has also resulted in the requirement for high input/high output farming and intensive management schemes. The impact of this on the environment has been significant, e.g. pollution problems arising from the need for high nitrogen fertilizers to produce sufficient high quality fodder, and disposal problems associated with slurry waste. Poorer areas of the community have been unable to compete with such farming systems, and are more suited to low input/low output farming using traditional stock. It is however the future perspective that is of greatest concern. It is impossible to predict requirements for cattle production - quality, production type, management systems, etc. The ability to switch rapidly to alternative production will be dependent on the genetic base of the population available to selection programs. It is therefore essential to maintain the greatest genetic diversity possible in the cattle population. Whilst current farming practices are perceived to be both efficient and acceptable, the breeds less favored by commercial farmers will dwindle. It is therefore important that on an European scale efficient management of these breeds maintains the widest genetic base possible. This project aims to carry out a survey of the current genetic base of the European cattle population and to provide the tools to assist breeding programs to maintain a broad base. The blood typing laboratories are now beginning to use micro-satellite markers as an alternative to serology for parentage verification, and are selecting a common set to be used from the several hundred micro-satellite markers available that cover the bovine genome, produced as part of the Bovine genome mapping project. Early work to measure genetic diversity used blood groups to show differences between breeds and the diversity present. Unfortunately, the number of loci available are limited, with only the B system being sufficiently polymorphic to be really useful. However, since there is a wealth of information available from such typing, this information can be used to estimate changes in the genetic structure of cattle populations across Europe over the past twenty years. More recently mini-satellite probes have been used to generate ''genetic fingerprints'' which have been used to show differences between individuals. Such fingerprints have been used to estimate genetic diversity - the greater the number of bands revealed by the fingerprint being equated with greater diversity. This is valid within limits. The main disadvantage of the fingerprint approach is that the chromosomal location and number of loci being sampled, and so the proportion of the genome examined, is unknown. The allelic bands on the gel cannot be easily identified, so allele inheritance cannot be addressed making it impossible to trace ancestry. Through the EC funded BovMaP project, large numbers of highly polymorphic micro-satellite markers have become available, which are being mapped on the bovine genome. These markers are particularly suited to measuring genetic diversity, and markers can be selected to cover the entire genome.

Proper citation: CaDBase: Genetic diversity in cattle (RRID:SCR_008146) Copy   

•   Source: SciCrunch Registry