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http://www.sugp.caltech.edu/SpBase/

SpBase is designed to present the results of the genome sequencing project for the purple sea urchin. The sequences and annotations emerging from this effort are organized in a database that provides the research community access to those data not normally presented through National Center for Biotechnology Information and other large databases. Additionally, the unique information on that links gene identities and sequences to the plate and well location to the library filters from the Sea Urchin genome Resource will also be presented. The software used to organize and present the sea urchin genome comes from GMOD, a collection of open source software tools for creating and managing genome-scale biological databases. That sea urchins eggs and embryos have long remained a popular research subject for cell and developmental biologists is one rationale for sequencing the genome. In addition, studies of embryonic development in the California Purple Sea Urchin, Strongylocentrotus purpuratus , have paralleled the emergence of molecular techniques ranging from the characterization of genomic repeat sequences in the 1970''s to the elucidation of gene regulatory networks in recent times. The parent of this site, SUGP, was meant to provide a focal point for the exchange of genomic information as the genome of the Purple sea urchin was being sequenced. Over these past years it has served as a repository for small sequencing projects and a source of sequence information useful for gene discovery projects. Here one could find information on macro-array libraries of cDNAs from the purple sea urchin and genomic DNA from several species. In addition, a Sequence Tag Connector (STC) collection has been assembled from 5% of the genome sequence and a very extensive repeat sequence catalog prepared. All of the sequence data that we maintained at SUGP was incorporated into the new SPBase. Of course, it is all in public sequence databases such as the National Center for Biological Information as well. Some additional sequence information is available at the Resource Center of the German Human Genome Project. With the publication of The Genome of the Sea Urchin Strongylocentrotus purpuratus by The Sea Urchin Genome Sequencing Consortium a link to the first 9941 gene annotations are now publicly available. The effort to sequence the whole purple sea urchin genome was a cooperative one that included contributions from the Sea Urchin Genome Facility here at the Center for Computational Regulatory Genomics, Beckman Institute, Caltech, and support from the Human Genome Research Institute of the National Institutes of Health. The sequencing was done at the Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas. Funding was approved based on an initiative submitted by the Sea Urchin Genome Advisory Committee.

Proper citation: SpBase - Strongylocentrotus purpuratus: the Sea Urchin Genome Database (RRID:SCR_007441) Copy   

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http://probeexplorer.cicancer.org/principal.php

Probe Explorer is an open access web-based bioinformatics application designed to show the association between microarray oligonucleotide probes and transcripts in the genomic context, but flexible enough to serve as a simplified genome and transcriptome browser. Coordinates and sequences of the genomic entities (loci, exons, transcripts), including vector graphics outputs, are provided for fifteen metazoa organisms and two yeasts. Alignment tools are used to built the associations between Affymetrix microarrays probe sequences and the transcriptomes (for human, mouse, rat and yeasts). Search by keywords is available and user searches and alignments on the genomes can also be done using any DNA or protein sequence query. Platform: Online tool

Proper citation: ProbeExplorer (RRID:SCR_007116) Copy   

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http://snpselector.duhs.duke.edu/hqsnp36.html

This is the HQSNP DB (high-quality SNP database) developed by CHG bioinformatics group. The high-quality SNP is defined as a SNP having allele frequency or genotyping data. The majority of the HQSNPs come from HapMap, others come from JSNP (Japanese SNP database), TSC (The SNP Consortium), Affymetrix 120K SNP, and Perlegen SNP. There are four kinds of SNP search you can do: * Get SNPs by dbSNP rs#: Choose this search if you have already selected a list of SNPs and you just want to get the SNP information. The program will generate a Excel file containing the SNP flanking sequence, variation, quality, function, etc. In the Excel file, there are 10 highlighted fields. You can send only those highlighted information to Illumina to get SNP pre-score. (The same fields are presented in other types of searches as well.) * Get gene SNPs by gene names: Choose this search if you have a list of gene names and you want to get the SNP information in these genes. The gene name can be official gene symbol, Ensembl gene ID, RefSeq accession ID, LocusLink number, etc. * Get gene SNPs by genome regions: Choose this search if you have a list of genome regions and you want to get all gene SNP information in these regions. The software will find all the Ensembl genes in the regions and find SNPs associated to each Ensembl gene. * Get genome scan SNPs by genome regions: Choose this search if you have a list of genome regions and you want to get evenly spaced SNPs in these regions. A SNP selection tool (SNPselector) was built upon HQSNP. It took snp ID list, gene name list, or genome region list as input and searched SNPs for genome scan or gene assoctiation study. It could take an optional ABI SNP file (exported from ABI SNP search web page) as input for checking whether the candidate SNP is available from ABI. It could also take an optional Illumina SNP pre-score file as input to select SNP for Illumina SNP assay. It generated results sorted by tag SNP in LD block, SNP quality, SNP function, SNP regulatory potential, and SNP mutation risk. SNPselector is now retired from public use (as of September 30, 2010).

Proper citation: High Quality SNP Database (RRID:SCR_007230) Copy   

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http://www.broadinstitute.org/annotation/tetraodon/

This database have been funded by the National Human Genome Research Institute (NHGRI) to produce shotgun sequence of the Tetraodon nigriviridis genome. The strategy involves Whole Genome Shotgun (WGS) sequencing, in which sequence from the entire genome is generated. Whole genome shotgun libraries were prepared from Tetraodon genomic DNA obtained from the laboratory of Jean Weissenbach at Genoscope. Additional sequence data of approximately 2.5X coverage of Tetraodon has also been generated by Genoscope in plasmid and BAC end reads. Broad and Genoscope intend to pool their data and generate whole genome assemblies. Tetraodon nigroviridis is a freshwater pufferfish of the order Tetraodontiformes and lives in the rivers and estuaries of Indonesia, Malaysia and India. This species is 20-30 million years distant from Fugu rubripes, a marine pufferfish from the same family. The gene repertoire of T. nigroviridis is very similar to that of other vertebrates. However, its relatively small genome of 385 Mb is eight times more compact than that of human, mostly because intergenic and intronic sequences are reduced in size compared to other vertebrate genomes. These genome characteristics along with the large evolutionary distance between bony fish and mammals make Tetraodon a compact vertebrate reference genome - a powerful tool for comparative genetics and for quick and reliable identification of human genes.

Proper citation: Tetraodon nigroviridis Database (RRID:SCR_007123) Copy   

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http://gelbank.anl.gov

GELBANK is a government project that provides an interactive interface for the comparison of 2DE patterns in the context of proteome sequence queries. Only proteomes of species with completed genomes (bacterial genomes, some eukaryotic genomes, human proteome) are presented in the database. The image database also contains not only scanned images, but also modeled gel patterns representing a collection of images (e.g. a master pattern for a sample). 2DE gel patterns are grouped by: tissue type, sample type, staining method used, separation technique used in the first dimension (by charge), the pH-range of the media used in first dimension, technique used in the second dimension (by size). Tools pertinent to the querying of two-dimensional gel-electrophoresis are implemented and integrated into database. When searching for sequences, tools that allow allow the discovery of sequences and alignment of multiple sequences are presented. Individual 2DE gel-patterns can be displayed or a collection of patterns can be animated.

Proper citation: GELBANK (RRID:SCR_007668) Copy   

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https://omictools.com/ecgene-tool

Database of functional annotation for alternatively spliced genes. It uses a gene-modeling algorithm that combines the genome-based expressed sequence tag (EST) clustering and graph-theoretic transcript assembly procedures. It contains genome, mRNA, and EST sequence data, as well as a genome browser application. Organisms included in the database are human, dog, chicken, fruit fly, mouse, rhesus, rat, worm, and zebrafish. Annotation is provided for the whole transcriptome, not just the alternatively spliced genes. Several viewers and applications are provided that are useful for the analysis of the transcript structure and gene expression. The summary viewer shows the gene summary and the essence of other annotation programs. The genome browser and the transcript viewer are available for comparing the gene structure of splice variants. Changes in the functional domains by alternative splicing can be seen at a glance in the transcript viewer. Two unique ways of analyzing gene expression is also provided. The SAGE tags deduced from the assembled transcripts are used to delineate quantitative expression patterns from SAGE libraries available publicly. The cDNA libraries of EST sequences in each cluster are used to infer qualitative expression patterns.

Proper citation: ECgene: Gene Modeling with Alternative Splicing (RRID:SCR_007634) Copy   

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http://degradome.uniovi.es

A database of human, chimpanzee, mouse, and rat proteases and protease inhibitors, as well as as the growing number of hereditary diseases caused by mutations in protease genes. Analysis of the human and mouse genomes has allowed us to annotate 581 human, 580 chimpanzee, 667 mouse, and 655 rat protease genes. Proteases are classified in five different classes according to their mechanism of catalysis. Proteases are a diverse and important group of enzymes representing >2% of the human, chimpanzee, mouse and rat genomes. This group of enzymes is implicated in numerous physiological processes. The importance of proteases is illustrated by the existence of 99 different hereditary diseases due to mutations in protease genes. Furthermore, proteases have been implicated in multiple human pathologies, including vascular diseases, rheumatoid arthritis, neurodegenerative processes, and cancer. During the last ten years, our laboratory has identified and characterized more than 60 human protease genes. Due to the importance of proteolytic enzymes in human physiology and pathology, we have recently introduced the concept of Degradome, as the complete repertoire of proteases expressed by a tissue or organism. Thanks to the recent completion of the human, chimpanzee, mouse, and rat genome sequencing projects, we were able to analyze and compare for the first time the complete protease repertoire in those mammalian organisms, as well as the complement of protease inhibitor genes. This webpage also contains the Supplementary Material of Human and mouse proteases: a comparative genomic approach Nat Rev Genet (2003) 4: 544-558, Genome sequence of the brown Norway rat yields insights into mammalian evolution Nature (2004) 428: 493-521, A genomic analysis of rat proteases and protease inhibitors Genome Res. (2004) 14: 609-622, and Comparative genomic analysis of human and chimpanzee proteases Genomics (2005) 86: 638-647.

Proper citation: Mammalian Degradome Database (RRID:SCR_007624) Copy   

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http://genomes.urv.es/HGT-DB/

The Horizontal Gene Transfer DataBase (HGT-DB) is a genomic database that includes statistical parameters such as G+C content, codon and amino-acid usage, as well as information about which genes deviate in these parameters for prokaryotic complete genomes. Under the hypothesis that genes from distantly related species have different nucleotide compositions, these deviated genes may have been acquired by horizontal gene transfer.

Proper citation: Horizontal Gene Transfer-DataBase (RRID:SCR_007706) Copy   

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http://img.jgi.doe.gov/

Datasets and tools for comparative analysis and annotation of all publicly available genomes from three domains of life in a uniquely integrated context. Plasmids that are not part of a specific microbial genome sequencing project and phage genomes are also included in order to increase its genomic context for comparative analysis. The user interface (see User Interface Map) allows navigating the microbial genome data space along its three key dimensions (genes, genomes, and functions), and groups together the main comparative analysis tools. Microbial genome data analysis in IMG usually starts with the definition of an analysis context in terms of selected genomes, functional annotations, and/or genes, followed by the individual or comparative analysis of genomes, functional annotations, or genes.

Proper citation: IMG (RRID:SCR_007733) Copy   

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http://spock.genes.nig.ac.jp/~genome/gtop.html

GTOP is a database consists of data analyses of proteins identified by various genome projects. This database mainly uses sequence homology analyses and features extensive utilization of information on three-dimensional structures. GTOP is built by the Laboratory of Gene-Product Informatics at the National Institute of Genetics. This research is supported by the Japan Science and Technology Corporation and Grants-in-Aid for Scientific Research (Genomes in category C) from the Ministry of Education, Science, Sports and Culture of Japan. We use the following methods: Prediction of 3D structure Sequence homology search of PDB, using REVERSE PSI-BLAST. Functional predictions (family classifications) Sequence homology search of Swiss-Prot, a well-annotated sequence database, with the use of BLAST. Other analytical methods We are also carrying out the following analyses: Motif Analysis(PROSITE) Family classification(Pfam) Prediction of transmembrane helix domains(SOSUI) Prediction of coiled-coil regions(Multicoil) Repetitive sequence analysis(RepAlign)

Proper citation: GTOP - Genomes To Protein structures (RRID:SCR_007698) Copy   

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https://leger2.helmholtz-hzi.de/cgi-bin/expLeger.pl

Knowledge database and visualization tool for comparative genomics of pathogenic and non-pathogenic Listeria species.Provides information on gene functions (as annotated or supposed by literature from homologous organisms) , protein expression levels under defined experimental conditions ,subcellular localization of proteins (expected and/or experimentally validated) , biological meaning of genes and proteins based on KEGG, InterPro and Gene Ontology.

Proper citation: LEGER: the post-genome Database for Listeria Research (RRID:SCR_007760) Copy   

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http://phylomedb.bioinfo.cipf.es

Database for phylomes, that is, complete collections of phylogenetic trees for all proteins encoded in a given genome. It aims at providing a repository of high-quality phylogenies and alignments for proteins encoded in model species. To derive a phylome, each protein encoded in a given genome is used as a seed to retrieve its homologs in other complete genomes. These sequences are aligned and processed to derive reliable phylogenies using several phylogenetic methods. Besides providing the evolutionary history of the gene families, phylomeDB includes phylogeny based predictions of orthology and paralogy relationships., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhylomeDB (RRID:SCR_007850) Copy   

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http://cmbi.bjmu.edu.cn/cmbidata/cgf/CGF_Database/cytokine.medic.kumamoto-u.ac.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. A collection of cDNA, gene and protein records of cytokines deposited in public databases provides various information about the cytokine members of vertebrates in other databases including NCBI GenBank, Swiss-Prot, UniGene, TIGR (The Institute for Genomic Research) Gene Indices, Ensembl, Entrez Gene, Mouse Genome Informatics (MGI) and Rat Genome Database (RGD). It also provides orthologous relationship of cytokine members and includes novel members identified in the databases.

Proper citation: Cytokine Family Database (RRID:SCR_008134) Copy   

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http://animal.dna.affrc.go.jp/agp/index.html

Database of comparative gene mapping between species to assist the mapping of the genes related to phenotypic traits in livestock. The linkage maps, cytogenetic maps, polymerase chain reaction primers of pig, cattle, mouse and human, and their references have been included in the database, and the correspondence among species have been stipulated in the database. AGP is an animal genome database developed on a Unix workstation and maintained by a relational database management system. It is a joint project of National Institute of Agrobiological Sciences (NIAS) and Institute of the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF-Institute), under cooperation with other related research institutes. AGP also contains the Pig Expression Data Explorer (PEDE), a database of porcine EST collections derived from full-length cDNA libraries and full-length sequences of the cDNA clones picked from the EST collection. The EST sequences have been clustered and assembled, and their similarity to sequences in RefSeq, and UniGene determined. The PEDE database system was constructed to store sequences and similarity data of swine full-length cDNA libraries and to make them available to users. It provides interfaces for keyword and ID searches of BLAST results and enables users to obtain sequence data and names of clones of interest. Putative SNPs in EST assemblies have been classified according to breed specificity and their effect on coding amino acids, and the assemblies are equipped with an SNP search interface. The database contains porcine nucleotide sequences and cDNA clones that are ready for analyses such as expression in mammalian cells, because of their high likelihood of containing full-length CDS. PEDE will be useful for researchers who want to explore genes that may be responsible for traits such as disease susceptibility. The database also offers information regarding major and minor porcine-specific antigens, which might be investigated in regard to the use of pigs as models in various medical research applications.

Proper citation: Animal Genome Database (RRID:SCR_008165) Copy   

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http://ccr.coriell.org/Sections/Collections/NHGRI/?SsId=11

DNA samples and cell lines from fifteen populations, including the samples used for the International HapMap Project, the HapMap 3 Project and the 1000 Genomes Project (except for the CEPH samples). All of the samples were contributed with consent to broad data release and to their use in many future studies, including for extensive genotyping and sequencing, gene expression and proteomics studies, and all other types of genetic variation research. NHGRI led the contribution of the NIH to the International HapMap Project, which developed a haplotype map of the human genome. This haplotype map, called the HapMap is a publicly available tool that allows researchers to find genes and genetic variations that affect health and disease. The samples from four populations used to develop the HapMap were initially housed in the Human Genetic Cell Repository of the National Institute of General Medical Sciences (NIGMS). Except for the Utah CEPH samples that were in the NIGMS Repository before the initiation of the HapMap Project and remain there, the NHGRI Repository now houses all of the HapMap samples. The NHGRI repository also houses the extended set of HapMap samples, which includes additional samples from the HapMap populations and samples from seven additional populations. All of the samples were collected with extensive community engagement, including discussions with members of the donor communities about the ethical and social implications of human genetic variation research. These samples were studied as part of the HapMap 3 Project. The NHGRI repository also houses the samples for the International 1000 Genomes Project. This Project is lightly sequencing genome-wide 2500 samples from 27 populations. This project aims to provide a detailed map of human genetic variation, including common and rare SNPs and structural variants. This map will allow more precise localization of genomic regions that contribute to health and disease. The 1000 Genomes Project includes many of the samples from the HapMap and extended set of HapMap samples, as well as samples being collected from additional populations. Currently, samples from five additional populations are available; the others will become available during 2011 and 2012. No identifying or phenotypic information is available for the samples. Donors gave broad consent for use of the samples, including for genotyping, sequencing, and cellular phenotype studies. Samples collected from other populations for the study of human genetic variation may be added to the collection in the future. The NHGRI Repository distributes high quality lymphoblastoid cell lines and DNA from the samples to researchers. DNA is provided in plates or panels of 70 to 100 samples or as individual samples. Cell cultures and DNA samples are distributed only to qualified professional persons who are associated with recognized research, medical, educational, or industrial organizations engaged in health-related research or health delivery.

Proper citation: NHGRI Sample Repository for Human Genetic Research (RRID:SCR_004528) Copy   

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http://www.cdc.gov/genomics/hugenet/default.htm

Human Genome Epidemiology Network, or HuGENet, is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable knowledge base of genetic associations and human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

Proper citation: Human Genome Epidemiology Network (RRID:SCR_013117) Copy   

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http://david.abcc.ncifcrf.gov/content.jsp?file=/ease/ease1.htm&type=1

Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible

Proper citation: EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) Copy   

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Ratings or validation data are available for this resource

https://www.gencodegenes.org

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

Proper citation: GENCODE (RRID:SCR_014966) Copy   

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https://www.ncbi.nlm.nih.gov/genbank/wgs/

Project for assemblies of incomplete genomes or incomplete chromosomes of prokaryotes or eukaryotes that are being sequenced by a whole genome shotgun strategy. WGS projects may be annotated, but annotation is not required. The nucleotide and protein data from all WGS projects go into the BLAST database.

Proper citation: Whole Genome Shotgun (WGS) Project (RRID:SCR_016637) Copy   

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http://www-sequence.stanford.edu/group/yeast_deletion_project/

Database and project to reveal open reading frames (ORFs) in the yeast genome in order to discover their functions. A PCR-based gene deletion strategy is used to assign functions through phenotypic analysis of mutants.

Proper citation: Saccharomyces Genome Deletion Project (RRID:SCR_014961) Copy   

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