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Found 220 result(s)
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<<<!!!<<< 2017-06-02: We recently suffered a server failure and are working to bring the full ORegAnno website back online. In the meantime, you may download the complete database here: http://www.oreganno.org/dump/ ; Data are also available through UCSC Genome Browser (e.g., hg38 -> Regulation -> ORegAnno) https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=686342163_2it3aVMQVoXWn0wuCjkNOVX39wxy&c=chr1&g=oreganno >>>!!!>>> The Open REGulatory ANNOtation database (ORegAnno) is an open database for the curation of known regulatory elements from scientific literature. Annotation is collected from users worldwide for various biological assays and is automatically cross-referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, the eVOC: Cell type ontology, and the Taxonomy database, where appropriate, with information regarding the original experimentation performed (evidence). ORegAnno further provides an open validation process for all regulatory annotation in the public domain. Assigned validators receive notification of new records in the database and are able to cross-reference the citation to ensure record integrity. Validators have the ability to modify any record (deprecating the old record and creating a new one) if an error is found. Further, any contributor to the database can comment on any annotation by marking errors, or adding special reports into function as they see fit. These features of ORegAnno ensure that the collection is of the highest quality and uniquely provides a dynamic view of our changing understanding of gene regulation in the various genomes.
The Reference Sequence (RefSeq) collection provides a comprehensive, integrated, non-redundant, well-annotated set of sequences, including genomic DNA, transcripts, and proteins. RefSeq sequences form a foundation for medical, functional, and diversity studies. They provide a stable reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis (especially RefSeqGene records), expression studies, and comparative analyses.
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The China National GeneBank database (CNGBdb) is a unified platform for biological big data sharing and application services. CNGBdb has now integrated a large amount of internal and external biological data from resources such as CNGB, NCBI, and the EBI. There are several sub-databases in CNGBdb, including literature, variation, gene, genome, protein, sequence, organism, project, sample, experiment, run, and assembly. Based on underlying big data and cloud computing technologies, it provides various data services, including archive, analysis, knowledge search, and management authorization of biological data. CNGBdb adopts data structures and standards of international omics, health, and medicine, such as The International Nucleotide Sequence Database Collaboration (INSDC), The Global Alliance for Genomics and Health GA4GH (GA4GH), Global Genome Biodiversity Network (GGBN), American College of Medical Genetics and Genomics (ACMG), and constructs standardized data and structures with wide compatibility. All public data and services provided by CNGBdb are freely available to all users worldwide. CNGB Sequence Archive (CNSA) is the bionomics data repository of CNGBdb. CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in life science, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, and Sequence. Moreover, CNSA has achieved the correlation of sample entities, sample information, and analyzed data on some projects. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.CNGB Sequence Archive (CNSA) is a convenient and efficient archiving system of multi-omics data in the life science of CNGBdb, which provides archiving services for raw sequencing reads and further analyzed results. CNSA follows the international data standards for omics data, and supports online and batch submission of multiple data types such as Project, Sample, Experiment/Run, Assembly, Variation, Metabolism, Single cell, Sequence. Its data submission service can be used as a supplement to the literature publishing process to support early data sharing.
PathCards is an integrated database of human biological pathways and their annotations. Human pathways were clustered into SuperPaths based on gene content similarity. Each PathCard provides information on one SuperPath which represents one or more human pathways.
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BacMap is a picture atlas of annotated bacterial genomes. It is an interactive visual database containing hundreds of fully labeled, zoomable, and searchable maps of bacterial genomes.
The NCBI Nucleotide database collects sequences from such sources as GenBank, RefSeq, TPA, and PDB. Sequences collected relate to genome, gene, and transcript sequence data, and provide a foundation for research related to the biomedical field.
BsubCyc is a model-organism database for the bacterium Bacillus subtilis and is based on the updated B. subtilis 168 genome sequence and annotation published by Barbe et al. in 2009. Gene function annotations are being updated when new literature is available.
The PeptideAtlas validates expressed proteins to provide eukaryotic genome data. Peptide Atlas provides data to advance biological discoveries in humans. The PeptideAtlas accepts proteomic data from high-throughput processes and encourages data submission.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
The NCBI database of Genotypes and Phenotypes archives and distributes the results of studies that have investigated the interaction of genotype and phenotype, including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits. The database provides summaries of studies, the contents of measured variables, and original study document text. dbGaP provides two types of access for users, open and controlled. Through the controlled access, users may access individual-level data such as phenotypic data tables and genotypes.
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.
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
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Database for identification and cataloguing of group II introns. All bacterial introns listed are full-length and appear to be functional, based on intron RNA and IEP characteristics. The database names the full-length introns, and provides information on their boundaries, host genes, and secondary structures. In addition, the website provides tools for analysis that may be useful to researchers who encounter group II introns in DNA sequences. Intron data can be downloaded in FASTA format.
The Drosophila Genetic Reference Panel (DGRP) is a population consisting of more than 200 inbred lines derived from the Raleigh, USA population. The DGRP is a living library of common polymorphisms affecting complex traits, and a community resource for whole genome association mapping of quantitative trait loci.
A database for plant breeders and researchers to combine, visualize, and interrogate the wealth of phenotype and genotype data generated by the Triticeae Coordinated Agricultural Project (TCAP).
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GABI, acronym for "Genomanalyse im biologischen System Pflanze", is the name of a large collaborative network of different plant genomic research projects. Plant data from different ‘omics’ fronts representing more than 10 different model or crop species are integrated in GabiPD.
MassBank of North America (MoNA) is a metadata-centric, auto-curating repository designed for efficient storage and querying of mass spectral records. It intends to serve as a the framework for a centralized, collaborative database of metabolite mass spectra, metadata and associated compounds. MoNA currently contains over 200,000 mass spectral records from experimental and in-silico libraries as well as from user contributions.
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Silkworm Pathogen Database (SilkPathDB) is a comprehensive resource for studying on pathogens of silkworm, including microsporidia, fungi, bacteria and virus. SilkPathDB provides access to not only genomic data including functional annotation of genes and gene products, but also extensive biological information for gene expression data and corresponding researches. SilkPathDB will be help with researches on pathogens of silkworm as well as other Lepidoptera insects.
TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.
<<<!!!<<< Effective May 2024, NCBI's Assembly resource will no longer be available. NCBI Assembly data can now be found on the NCBI Datasets genome pages. https://www.re3data.org/repository/r3d100014298 >>>!!!>>> A database providing information on the structure of assembled genomes, assembly names and other meta-data, statistical reports, and links to genomic sequence data.
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DEG hosts records of currently available essential genomic elements, such as protein-coding genes and non-coding RNAs, among bacteria, archaea and eukaryotes. Essential genes in a bacterium constitute a minimal genome, forming a set of functional modules, which play key roles in the emerging field, synthetic biology.
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
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The goals of FMGP are to: (i) sequence complete mitochondrial genomes from all major fungal lineages, (ii) infer a robust fungal phylogeny, (iii) define the origin of the fungi, their protistan ancestors, and their specific phylogenetic link to the animals, (iv) investigate mitochondrial gene expression, introns, RNAse P RNA structures, mobile elements.