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Found 61 result(s)

Mammalian Transcriptomic Database

MTD

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MTD is focused on mammalian transcriptomes with a current version that contains data from humans, mice, rats and pigs. Regarding the core features, the MTD browses genes based on their neighboring genomic coordinates or joint KEGG pathway and provides expression information on exons, transcripts, and genes by integrating them into a genome browser. We developed a novel nomenclature for each transcript that considers its genomic position and transcriptional features.

PeanutBase

Genetic and genomic data to enable more rapid crop improvement in peanut

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PeanutBase is a peanut community resource providing genetic, genomic, gene function, and germplasm data to support peanut breeding and molecular research. This includes molecular markers, genetic maps, QTL data, genome assemblies, germplasm records, and traits. Data is curated from literature and submitted directly by researchers. Funding for PeanutBase is provided by the Peanut Foundation with in-kind contributions from the USDA-ARS.

PiroplasmaDB

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A genome database for the genus Piroplasma. PiroplasmaDB is a member of pathogen-databases that are housed under the NIAID-funded EuPathDB Bioinformatics Resource Center (BRC) umbrella.

CancerModels.Org

formerly; Patients-derived tumor xenograft finder

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Patients-derived tumor xenograft (PDX) mouse models are an important oncology research platform to study tumor evolution, drug response and personalised medicine approaches. We have expanded to organoids and cell lines and are now called CancerModels.Org

Cancer Genomics Hub

CGHub

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>>>>!!!!<<<< The Cancer Genomics Hub mission is now completed. The Cancer Genomics Hub was established in August 2011 to provide a repository to The Cancer Genome Atlas, the childhood cancer initiative Therapeutically Applicable Research to Generate Effective Treatments and the Cancer Genome Characterization Initiative. CGHub rapidly grew to be the largest database of cancer genomes in the world, storing more than 2.5 petabytes of data and serving downloads of nearly 3 petabytes per month. As the central repository for the foundational genome files, CGHub streamlined team science efforts as data became as easy to obtain as downloading from a hard drive. The convenient access to Big Data, and the collaborations that CGHub made possible, are now essential to cancer research. That work continues at the NCI's Genomic Data Commons. All files previously stored at CGHub can be found there. The Website for the Genomic Data Commons is here: https://gdc.nci.nih.gov/ >>>>!!!!<<<< The Cancer Genomics Hub (CGHub) is a secure repository for storing, cataloging, and accessing cancer genome sequences, alignments, and mutation information from the Cancer Genome Atlas (TCGA) consortium and related projects. Access to CGHub Data: All researchers using CGHub must meet the access and use criteria established by the National Institutes of Health (NIH) to ensure the privacy, security, and integrity of participant data. CGHub also hosts some publicly available data, in particular data from the Cancer Cell Line Encyclopedia. All metadata is publicly available and the catalog of metadata and associated BAMs can be explored using the CGHub Data Browser.

The Adaptive Evolution Database

TAED

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TAED is a database of phylogenetically indexed gene families. It contains multiple sequence alignments from MAFFT1, maximum likelihood phylogenetic trees from PhyML2, bootstrap values for each node, dN/dS ratios for each lineage from the free ratios model in PAML3, and labels for each node of speciation or duplication from gene tree/species tree reconciliation using SoftParsMap4. The phylogenetic indexing enables simultaneous viewing of lineages with high dN/dS that occurred along the same species tree branches. Resources from the Protein Data Bank (PDB) and the Kyoto Encyclopedia of Genes and Genomes (KEGG)5, have been incorporated into the TAED analysis to detect substitutions along each branch within the phylogenetic tree and to assess selection within pathways.

Cancer GenomeAtlas Data Portal

Cancer Genome Atlas Data Portal

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The Cancer Genome Atlas (TCGA) Data Portal provides a platform for researchers to search, download, and analyze data sets generated by TCGA. It contains clinical information, genomic characterization data, and high level sequence analysis of the tumor genomes. The Data Coordinating Center (DCC) is the central provider of TCGA data. The DCC standardizes data formats and validates submitted data.

MG-RAST

Metagenomics analysis server

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The MG-RAST server is an open source system for annotation and comparative analysis of metagenomes. Users can upload raw sequence data in fasta format; the sequences will be normalized and processed and summaries automatically generated. The server provides several methods to access the different data types, including phylogenetic and metabolic reconstructions, and the ability to compare the metabolism and annotations of one or more metagenomes and genomes. In addition, the server offers a comprehensive search capability. Access to the data is password protected, and all data generated by the automated pipeline is available for download in a variety of common formats. MG-RAST has become an unofficial repository for metagenomic data, providing a means to make your data public so that it is available for download and viewing of the analysis without registration, as well as a static link that you can use in publications. It also requires that you include experimental metadata about your sample when it is made public to increase the usefulness to the community.

FlyBase

A Database of Drosophila Genes and Genomes

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FlyBase is a database of genetic, genomic and functional data for Drosophila species, with a focus on the model organism Drosophila melanogaster.FlyBase contains a complete annotation of the Drosophila melanogaster genome that is updated several times per year.It also includes a searchable bibliography of research on Drosophila genetics in the last century. The site also provides a large database of images illustrating the full genome, and several movies detailing embryogenesis.

IMGT/GENE-DB

ImMunoGeneTics / Gene-DB

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IMGT/GENE-DB is the IMGT genome database for IG and TR genes from human, mouse and other vertebrates. IMGT/GENE-DB provides a full characterization of the genes and of their alleles: IMGT gene name and definition, chromosomal localization, number of alleles, and for each allele, the IMGT allele functionality, and the IMGT reference sequences and other sequences from the literature. IMGT/GENE-DB allele reference sequences are available in FASTA format (nucleotide and amino acid sequences with IMGT gaps according to the IMGT unique numbering, or without gaps).

Expression Atlas

Gene Expression Atlas

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The Expression Atlas provides information on gene expression patterns under different biological conditions such as a gene knock out, a plant treated with a compound, or in a particular organism part or cell. It includes both microarray and RNA-seq data. The data is re-analysed in-house to detect interesting expression patterns under the conditions of the original experiment. There are two components to the Expression Atlas, the Baseline Atlas and the Differential Atlas. The Baseline Atlas displays information about which gene products are present (and at what abundance) in "normal" conditions (e.g. tissue, cell type). It aims to answer questions such as "which genes are specifically expressed in human kidney?". This component of the Expression Atlas consists of highly-curated and quality-checked RNA-seq experiments from ArrayExpress. It has data for many different animal and plant species. New experiments are added as they become available. The Differential Atlas allows users to identify genes that are up- or down-regulated in a wide variety of different experimental conditions such as yeast mutants, cadmium treated plants, cystic fibrosis or the effect on gene expression of mind-body practice. Both microarray and RNA-seq experiments are included in the Differential Atlas. Experiments are selected from ArrayExpress and groups of samples are manually identified for comparison e.g. those with wild type genotype compared to those with a gene knock out. Each experiment is processed through our in-house differential expression statistical analysis pipeline to identify genes with a high probability of differential expression.