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Found 20 result(s)
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
FungiDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for the kingdom Fungi. FungiDB was first released in early 2011 as a collaborative project between EuPathDB and the group of Jason Stajich (University of California, Riverside). At the end of 2015, FungiDB was integrated into the EuPathDB bioinformatic resource center. FungiDB integrates whole genome sequence and annotation and also includes experimental and environmental isolate sequence data. The database includes comparative genomics, analysis of gene expression, and supplemental bioinformatics analyses and a web interface for data-mining.
As with most biomedical databases, the first step is to identify relevant data from the research community. The Monarch Initiative is focused primarily on phenotype-related resources. We bring in data associated with those phenotypes so that our users can begin to make connections among other biological entities of interest. We import data from a variety of data sources. With many resources integrated into a single database, we can join across the various data sources to produce integrated views. We have started with the big players including ClinVar and OMIM, but are equally interested in boutique databases. You can learn more about the sources of data that populate our system from our data sources page https://monarchinitiative.org/about/sources.
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
TriTrypDB is an integrated genomic and functional genomic database for pathogens of the family Trypanosomatidae, including organisms in both Leishmania and Trypanosoma genera. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
VectorBase provides data on arthropod vectors of human pathogens. Sequence data, gene expression data, images, population data, and insecticide resistance data for arthropod vectors are available for download. VectorBase also offers genome browser, gene expression and microarray repository, and BLAST searches for all VectorBase genomes. VectorBase Genomes include Aedes aegypti, Anopheles gambiae, Culex quinquefasciatus, Ixodes scapularis, Pediculus humanus, Rhodnius prolixus. VectorBase is one the Bioinformatics Resource Centers (BRC) projects which is funded by National Institute of Allergy and Infectious Diseases (NAID).
<<<!!!<<< Effective May 2024, NCBI's Genome resource will no longer be available. NCBI Genome data can now be found on the NCBI Datasets taxonomy pages. https://www.re3data.org/repository/r3d100014298 >>>!!!>>> The Genome database contains annotations and analysis of eukaryotic and prokaryotic genomes, as well as tools that allow users to compare genomes and gene sequences from humans, microbes, plants, viruses and organelles. Users can browse by organism, and view genome maps and protein clusters.
<<<!!!<<< The repository is no longer available - Data previously on the site are now available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/mhc/Final Archive. >>>!!!>>> The dbMHC database provides an open, publicly accessible platform for DNA and clinical data related to the human Major Histocompatibility Complex (MHC). The dbMHC provides access to human leukocyte antigen (HLA) sequences, HLA allele and haplotype frequencies, and clinical datasets.
VertNet is a NSF-funded collaborative project that makes biodiversity data free and available on the web. VertNet is a tool designed to help people discover, capture, and publish biodiversity data. It is also the core of a collaboration between hundreds of biocollections that contribute biodiversity data and work together to improve it. VertNet is an engine for training current and future professionals to use and build upon best practices in data quality, curation, research, and data publishing. Yet, VertNet is still the aggregate of all of the information that it mobilizes. To us, VertNet is all of these things and more.
The Maize Genetics and Genomics Database focuses on collecting data related to the crop plant and model organism Zea mays. The project's goals are to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models. MaizeGDB also aims to make the Maize Newsletter available, and provide support services to the community of maize researchers. MaizeGDB is working with the Schnable lab, the Panzea project, The Genome Reference Consortium, and iPlant Collaborative to create a plan for archiving, dessiminating, visualizing, and analyzing diversity data. MMaizeGDB is short for Maize Genetics/Genomics Database. It is a USDA/ARS funded project to integrate the data found in MaizeDB and ZmDB into a single schema, develop an effective interface to access this data, and develop additional tools to make data analysis easier. Our goal in the long term is a true next-generation online maize database.aize genetics and genomics database.
The HomoloGene database provides a system for the automated detection of homologs among annotated genes of genomes across multiple species. These homologs are fully documented and organized by homology group. HomoloGene processing uses proteins from input organisms to compare and sequence homologs, mapping back to corresponding DNA sequences.
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>>>!!!<<< The NCI Cancer Models Database, caMOD, was retired on December 24, 2015. Information about many of the mouse models hosted in caMOD was obtained from the Jackson Laboratory Mouse Tumor Biology (MTB) Database and can be accessed through that resource http://tumor.informatics.jax.org/mtbwi/index.do . See caMOD Retirement Announcement https://wiki.nci.nih.gov/display/caMOD/caMOD+Retirement+Announcement >>>>!!<<< Query the Cancer Models database for models submitted by fellow researchers. Retrieve information about the making of models, their genetic description, histopathology, derived cell lines, associated images, carcinogenic agents, and therapeutic trials. Links to associated publications and other resources are provided.
The Electron Microscopy Data Bank (EMDB) is a public repository for electron microscopy density maps of macromolecular complexes and subcellular structures. It covers a variety of techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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The Chickpea Transcriptome Database (CTDB) has been developed with the view to provide most comprehensive information about the chickpea transcriptome, the most relevant part of the genome. The database contains various information and tools for transcriptome sequence, functional annotation, conserved domain(s), transcription factor families, molecular markers (microsatellites and single nucleotide polymorphisms), Comprehensive gene expression and comparative genomics with other legumes. The database is a freely available resource, which provides user scientists/breeders a portal to search, browse and query the data to facilitate functional and applied genomics research in chickpea and other legumes. The current release of database provides transcriptome sequence from cultivated (Cicer arietinum desi (ICC4958) and kabuli (ICCV2)) and wild (Cicer reticulatum, PI489777) chickpea genotypes.
The Allele Frequency Net Database (AFND) is a public database which contains frequency information of several immune genes such as Human Leukocyte Antigens (HLA), Killer-cell Immunoglobulin-like Receptors (KIR), Major histocompatibility complex class I chain-related (MIC) genes, and a number of cytokine gene polymorphisms. The Allele Frequency Net Database (AFND) provides a central source, freely available to all, for the storage of allele frequencies from different polymorphic areas in the Human Genome. Users can contribute the results of their work into one common database and can perform database searches on information already available. We have currently collected data in allele, haplotype and genotype format. However, the success of this website will depend on you to contribute your data.
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Stemformatics is a collaboration between the stem cell and bioinformatics community. We were motivated by the plethora of exciting cell models in the public and private domains, and the realisation that for many biologists these were mostly inaccessible. We wanted a fast way to find and visualise interesting genes in these exemplar stem cell datasets. We'd like you to explore. You'll find data from leading stem cell laboratories in a format that is easy to search, easy to visualise and easy to export.
The BBS is a cooperative effort between the U.S. Geological Survey's Patuxent Wildlife Research Center and Environment Canada's Canadian Wildlife Service to monitor the status and trends of North American bird populations. Following a rigorous protocol, BBS data are collected by thousands of dedicated participants along thousands of randomly established roadside routes throughout the continent. Professional BBS coordinators and data managers work closely with researchers and statisticians to compile and deliver these population data and population trend analyses on more than 400 bird species, for use by conservation managers, scientists, and the general public.
Ag Data Commons provides access to a wide variety of open data relevant to agricultural research. We are a centralized repository for data already on the web, as well as for new data being published for the first time. While compliance with the U.S. Federal public access and open data directives is important, we aim to surpass them. Our goal is to foster innovative data re-use, integration, and visualization to support bigger, better science and policy.
The Yeast Resource Center provides access to data about mass spectrometry, yeast two-hybrid arrays, deconvolution florescence microscopy, protein structure prediction and computational biology. These services are provided to further the goal of a complete understanding of the chemical interactions required for the maintenance and faithful reproduction of a living cell. The observation that the fundamental biological processes of yeast are conserved among all eukaryotes ensures that this knowledge will shape and advance our understanding of living systems.