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Found 28 result(s)
We are a leading international centre for genomics and bioinformatics research. Our mandate is to advance knowledge about cancer and other diseases, to improve human health through disease prevention, diagnosis and therapeutic approaches, and to realize the social and economic benefits of genomics research.
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.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
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.
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The Human Genetic Variation Database (HGVD) aims to provide a central resource to archive and display Japanese genetic variation and association between the variation and transcription level of genes. The database currently contains genetic variations determined by exome sequencing of 1,208 individuals and genotyping data of common variations obtained from a cohort of 3,248 individuals.
!!! >>> the repository is offline >>> !!! GOBASE is a taxonomically broad organelle genome database that organizes and integrates diverse data related to mitochondria and chloroplasts. GOBASE is currently expanding to include information on representative bacteria that are thought to be specifically related to the bacterial ancestors of mitochondria and chloroplasts
OrtholugeDB contains Ortholuge-based orthology predictions for completely sequenced bacterial and archaeal genomes. It is also a resource for reciprocal best BLAST-based ortholog predictions, in-paralog predictions (recently duplicated genes) and ortholog groups in Bacteria and Archaea. The Ortholuge method improves the specificity of high-throughput orthology prediction.
BiGG is a knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.
Giardia lamblia is a significant, environmentally transmitted, human pathogen and an amitochondriate protist. It is a major contributor to the enormous worldwide burden of human diarrheal diseases, yet the basic biology of this parasite is not well understood. No virulence factor has been identified. The Giardia lamblia genome contains only 12 million base pairs distributed onto five chromosomes. Its analysis promises to provide insights about the origins of nuclear genome organization, the metabolic pathways used by parasitic protists, and the cellular biology of host interaction and avoidance of host immune systems. Since the divergence of Giardia lamblia lies close to the transition between eukaryotes and prokaryotes in universal ribosomal RNA phylogenies, it is a valuable, if not unique, model for gaining basic insights into genetic innovations that led to formation of eukaryotic cells. In evolutionary terms, the divergence of this organism is at least twice as ancient as the common ancestor for yeast and man. A detailed study of its genome will provide insights into an early evolutionary stage of eukaryotic chromosome organization as well as other aspects of the prokaryotic / eukaryotic divergence.
GeneCards is a searchable, integrative database that provides comprehensive, user-friendly information on all annotated and predicted human genes. It automatically integrates gene-centric data from ~125 web sources, including genomic, transcriptomic, proteomic, genetic, clinical and functional information.
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The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), advances life & health sciences by providing open access to a suite of resources, with the aim to translate big data into big discoveries and support worldwide activities in both academia and industry.
ArrayExpress is one of the major international repositories for high-throughput functional genomics data from both microarray and high-throughput sequencing studies, many of which are supported by peer-reviewed publications. Data sets are submitted directly to ArrayExpress and curated by a team of specialist biological curators. In the past (until 2018) datasets from the NCBI Gene Expression Omnibus database were imported on a weekly basis. Data is collected to MIAME and MINSEQE standards.
DDBJ; DNA Data Bank of Japan is the sole nucleotide sequence data bank in Asia, which is officially certified to collect nucleotide sequences from researchers and to issue the internationally recognized accession number to data submitters.Since we exchange the collected data with EMBL-Bank/EBI; European Bioinformatics Institute and GenBank/NCBI; National Center for Biotechnology Information on a daily basis, the three data banks share virtually the same data at any given time. The virtually unified database is called "INSD; International Nucleotide Sequence Database DDBJ collects sequence data mainly from Japanese researchers, but of course accepts data and issue the accession number to researchers in any other countries.
The Cancer Cell Line Encyclopedia project is a collaboration between the Broad Institute, and the Novartis Institutes for Biomedical Research and its Genomics Institute of the Novartis Research Foundation to conduct a detailed genetic and pharmacologic characterization of a large panel of human cancer models, to develop integrated computational analyses that link distinct pharmacologic vulnerabilities to genomic patterns and to translate cell line integrative genomics into cancer patient stratification. The CCLE provides public access to genomic data, analysis and visualization for about 1000 cell lines.
BioGPS is a gene portal built with two guiding principles in mind -- customizability and extensibility. It is a complete resource for learning about gene and protein function. A free extensible and customizable gene annotation portal, a complete resource for learning about gene and protein function.
The 1000 Genomes Project is an international collaboration to produce an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts. This resource will support genome-wide association studies and other medical research studies. The genomes of about 2500 unidentified people from about 25 populations around the world will be sequenced using next-generation sequencing technologies. The results of the study will be freely and publicly accessible to researchers worldwide. The International Genome Sample Resource (IGSR) has been established at EMBL-EBI to continue supporting data generated by the 1000 Genomes Project, supplemented with new data and new analysis.
>>>!!!<<< Sorry.we are no longer in operation >>>!!!<<< The Beta Cell Biology Consortium (BCBC) was a team science initiative that was established by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). It was initially funded in 2001 (RFA DK-01-014), and competitively continued both in 2005 (RFAs DK-01-17, DK-01-18) and in 2009 (RFA DK-09-011). Funding for the BCBC came to an end on August 1, 2015, and with it so did our ability to maintain active websites.!!! One of the many goals of the BCBC was to develop and maintain databases of useful research resources. A total of 813 different scientific resources were generated and submitted by BCBC investigators over the 14 years it existed. Information pertaining to 495 selected resources, judged to be the most scientifically-useful, has been converted into a static catalog, as shown below. In addition, the metadata for these 495 resources have been transferred to dkNET in the form of RDF descriptors, and all genomics data have been deposited to either ArrayExpress or GEO. Please direct questions or comments to the NIDDK Division of Diabetes, Endocrinology & Metabolic Diseases (DEM).
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>>>!!!<<< OMICtools is no longer online >>>!!!<<< We founded OMICtools in 2012 with the vision to drive progress in life science. We wanted to empower life science practitioners all over the world to achieve breakthroughs by getting data to talk. While we made tremendous progress over the past three years, developing a bioinformatics database of software and dynamic protocols, attracting more than 1.5M visitors a year, we lacked the financial support we needed to continue. We certainly gave it our all. We'd like to thank everyone who believed in us and supported us on this journey: all our users, our community, our friends, families and employees (who we consider as our extended family!). omicX will probably shut down its operations within the next few weeks. The team and I remain firmly committed to our vision, particularly at this very difficult time. It is now, more than ever before, that researchers need access to a resource that pools collective scientific intelligence. We have accumulated an awful lot of experience which we are keen to share. If your institution would be interested in taking over our website and database, to provide researchers with continued access to the platform, or you simply want to stay in touch with the omicX team, contact us at contact@omictools.com or at carine.toutain@fhbx.eu.
GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, and create collaborative projects using the Collaborative Workspace. GeneLab promises to facilitate and improve information sharing, foster innovation, and increase the pace of scientific discovery from extremely rare and valuable space biology experiments. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight. GeneLab helps scientists understand how the fundamental building blocks of life itself – DNA, RNA, proteins, and metabolites – change from exposure to microgravity, radiation, and other aspects of the space environment. GeneLab does so by providing fully coordinated epigenomics, genomics, transcriptomics, proteomics, and metabolomics data alongside essential metadata describing each spaceflight and space-relevant experiment. By carefully curating and implementing best practices for data standards, users can combine individual GeneLab datasets to gain new, comprehensive insights about the effects of spaceflight on biology. In this way, GeneLab extends the scientific knowledge gained from each biological experiment conducted in space, allowing scientists from around the world to make novel discoveries and develop new hypotheses from these priceless data.