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Found 106 result(s)
AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals’ transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated.
ALFRED is a free, web-accessible, curated compilation of allele frequency data on DNA sequence polymorphisms in anthropologically defined human populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation.
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.
AmoebaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for Entamoeba and Acanthamoeba parasites. In its first iteration (released in early 2010), AmoebaDB contains the genomes of three Entamoeba species (see below). AmoebaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers . The database includes supplemental bioinformatics analyses and a web interface for data-mining.
Genome track alignments using GBrowse on this site are featured with: (1) Annotated and predicted genes and transcripts; (2) QTL / SNP Association tracks; (3) OMIA genes; (4) Various SNP Chip tracks; (5) Other mapping fetures or elements that are available.
The Antimicrobial Peptide Database (APD) was originally created by a graduate student, Zhe Wang, as his master's thesis in the laboratory of Dr. Guangshun Wang. The project was initiated in 2002 and the first version of the database was open to the public in August 2003. It contained 525 peptide entries, which can be searched in multiple ways, including APD ID, peptide name, amino acid sequence, original location, PDB ID, structure, methods for structural determination, peptide length, charge, hydrophobic content, antibacterial, antifungal, antiviral, anticancer, and hemolytic activity. Some results of this bioinformatics tool were reported in the 2004 database paper. The peptide data stored in the APD were gleaned from the literature (PubMed, PDB, Google, and Swiss-Prot) manually in over a decade.
ArkDB is a generic, species-independent database built to capture the state of published information on genome mapping in a given species. It stores details of references, markers and loci and genetic linkage and cytogenetic maps which can be drawn using the online map-drawing application. Data from linkage maps held within the ArkDB system can be drawn alongside their corresponding genome sequence maps (extracted from ENSEMBL).
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The goal of the Autophagy Database is to provide up-to-date relevant information including protein structure data to researchers of autophagy, and to disseminate important findings to a wider audience so that their ramifications can be appreciated. For this purpose, we strive to make the database to contain as much pertinent information as possible and to make the contents freely available in a user-friendly format.
BCSDB database is aimed at provision of structural, bibliographic, taxonomic and related information on bacterial carbohydrate structures. Two key points of this service are: covering - is above 90% in the scope of bacterial carbohydrates. This means the negative search answer remains valuable scientific information. And consistence - we manually check the data, and aim at hight quality error-free content. The main source of data is a retrospective literature analysis. About 25% of data were imported from CCSD (Carbbank, ceased in 1997, University of Georgia, Athens; structures published before 1995) with subsequent manual curation and approval. Current coverage is displayed in red on the top of the left menu. The time lag between publication of new data and their deposition ~ 1 year. The scope is "bacterial carbohydrates" and covers nearly all structures of this class published up to 2016. Bacterial means that a structure has been found in bacteria or obtained by modification of those found in bacteria. Carohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds, in which at least one residue is a sugar or its derivative.
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Bacteriome.org is a database integrating physical (protein-protein) and functional interactions within the context of an E. coli knowledgebase.
BBMRI-ERIC is a European research infrastructure for biobanking. We bring together all the main players from the biobanking field – researchers, biobankers, industry, and patients – to boost biomedical research. To that end, we offer quality management services, support with ethical, legal and societal issues, and a number of online tools and software solutions. Ultimately, our goal is to make new treatments possible. The Directory is a tool to share aggregate information about the biobanks that are willing external collaboration. It is based on the MIABIS 2.0 standard, which describes the samples and data in the biobanks at an aggregated level.
!!!!! This database doesn't exist anymore. 2017-09-05 !!!!!BeetleBase is a comprehensive sequence database and important community resource for Tribolium genetics, genomics and developmental biology. It provides genetic data on the Tribolium Castaneum, Red Flour Beetle, as gene maps, official gene set, reference sequences, predicted models, and whole-genome tiling array representing developmental stages.
The Benchmark Energy & Geometry Database (BEGDB) collects results of highly accurate QM calculations of molecular structures, energies and properties. These data can serve as benchmarks for testing and parameterization of other computational methods.
British Antarctic Survey (BAS) has, for over 60 years, undertaken the majority of Britain's scientific research on and around the Antarctic continent. Atmospheric, biosphere, cryosphere, geosphere, hydrosphere, and Sun-Earth interactions metadata and data are available. Geographic information and collections are highlighted as well. Information and mapping services include a Discovery Metadata System, Data Access System, the Antarctic Digital Database (ADD), Geophysics Data Portal (BAS-GDP), ICEMAR, a fossil database, and the Antarctic Plant Database.
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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.
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>>>!!!<<<As stated 2017-05-23 Cancer GEnome Mine is no longer available >>>!!!<<< Cancer GEnome Mine is a public database for storing clinical information about tumor samples and microarray data, with emphasis on array comparative genomic hybridization (aCGH) and data mining of gene copy number changes.
This is CSDB version 1 merged from Bacterial (BCSDB) and Plant&Fungal (PFCSDB) databases. This database aims at provision of structural, bibliographic, taxonomic, NMR spectroscopic and other information on glycan and glycoconjugate structures of prokaryotic, plant and fungal origin. It has been merged from the Bacterial and Plant&Fungal Carbohydrate Structure Databases (BCSDB+PFCSDB). The key points of this service are: High coverage. The coverage for bacteria (up to 2016) and archaea (up to 2016) is above 80%. Similar coverage for plants and fungi is expected in the future. The database is close to complete up to 1998 for plants, and up to 2006 for fungi. Data quality. High data quality is achieved by manual curation using original publications which is assisted by multiple automatic procedures for error control. Errors present in publications are reported and corrected, when possible. Data from other databases are verified on import. Detailed annotations. Structural data are supplied with extended bibliography, assigned NMR spectra, taxon identification including strains and serogroups, and other information if available in the original publication. Services. CSDB serves as a platform for a number of computational services tuned for glycobiology, such as NMR simulation, automated structure elucidation, taxon clustering, 3D molecular modeling, statistical processing of data etc. Integration. CSDB is cross-linked to other glycoinformatics projects and NCBI databases. The data are exportable in various formats, including most widespread encoding schemes and records using GlycoRDF ontology. Free web access. Users can access the database for free via its web interface (see Help). The main source of data is retrospective literature analysis. About 20% of data were imported from CCSD (Carbbank, University of Georgia, Athens; structures published before 1996) with subsequent manual curation and approval. The current coverage is displayed in red on the top of the left menu. The time lag between the publication of new data and their deposition into CSDB is ca. 1 year. In the scope of bacterial carbohydrates, CSDB covers nearly all structures of this origin published up to 2016. Prokaryotic, plant and fungal means that a glycan was found in the organism(s) belonging to these taxonomic domains or was obtained by modification of those found in them. Carbohydrate means a structure composed of any residues linked by glycosidic, ester, amidic, ketal, phospho- or sulpho-diester bonds in which at least one residue is a sugar or its derivative.
CCRIS contains over 9,000 chemical records with carcinogenicity, mutagenicity, tumor promotion, and tumor inhibition test results. Data are derived from studies cited in primary journals, current awareness tools, NCI reports, and other special sources. Test results have been reviewed by experts in carcinogenesis and mutagenesis. >CCRIS provides historical information from the years 1985 - 2011. It is no longer updated.< CCRIS is accessible, free of charge, via TOXNET at: https://toxnet/nlm.nih.gov
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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.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
The CPTAC Data Portal is the centralized repository for the dissemination of proteomic data collected by the Proteome Characterization Centers (PCCs) for the CPTAC program. The portal also hosts analyses of the mass spectrometry data (mapping of spectra to peptide sequences and protein identification) from the PCCs and from a CPTAC-sponsored common data analysis pipeline (CDAP).
CODEX is a database of NGS mouse and human experiments. Although, the main focus of CODEX is Haematopoiesis and Embryonic systems, the database includes a large variety of cell types. In addition to the publically available data, CODEX also includes a private site hosting non-published data. CODEX provides access to processed and curated NGS experiments. To use CODEX: (i) select a specialized repository (HAEMCODE or ESCODE) or choose the whole compendium (CODEX), then (ii) filter by organism and (iii) choose how to explore the database.
The Comparative RNA Web (CRW) Site disseminates information about RNA structure and evolution that has been determined using comparative sequence analysis. We present both raw (sequences, structure models, metadata) and processed (analyses, evolution, accuracy) data, organized into four main sections.