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Found 52 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.
Addgene archives and distributes plasmids for researchers around the globe. They are working with thousands of laboratories to assemble a high-quality library of published plasmids for use in research and discovery. By linking plasmids with articles, scientists can always find data related to the materials they request.
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.
>>>!!!<<< As stated 2017-05-16 The BIRN project was finished a few years ago. The web portal is no longer live.>>>!!!<<< BIRN is a national initiative to advance biomedical research through data sharing and online collaboration. It supports multi-site, and/or multi-institutional, teams by enabling researchers to share significant quantities of data across geographic distance and/or incompatible computing systems. BIRN offers a library of data-sharing software tools specific to biomedical research, best practice references, expert advice and other resources.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.
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.
>>>!!!<<< Noticed 26.08.2020: The NCI CBIIT instance of the CGAP no longer exist on this website. The Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer has a new home at the NCI-funded Institute for Systems Biology Cancer Genomics Cloud available at the following location: https://mitelmandatabase.isb-cgc.org >>>!!!<<<
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.
>>>>!!!!<<<< 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.
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We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes.For both Chromatin- immunoprecipation Transcription Factors and Histone modifications. Sequence files and the associated probability files are also provided.
Complete Genomics provides free public access to a variety of whole human genome data sets generated from Complete Genomics’ sequencing service. The research community can explore and familiarize themselves with the quality of these data sets, review the data formats provided from our sequencing service, and augment their own research with additional summaries of genomic variation across a panel of diverse individuals. The quality of these data sets is representative of what a customer can expect to receive for their own samples. This public genome repository comprises genome results from both our Standard Sequencing Service (69 standard, non-diseased samples) and the Cancer Sequencing Service (two matched tumor and normal sample pairs). In March 2013 Complete Genomics was acquired by BGI-Shenzhen , the world’s largest genomics services company. BGI is a company headquartered in Shenzhen, China that provides comprehensive sequencing and bioinformatics services for commercial science, medical, agricultural and environmental applications. Complete Genomics is now focused on building a new generation of high-throughput sequencing technology and developing new and exciting research, clinical and consumer applications.
The Conserved Domain Database is a resource for the annotation of functional units in proteins. Its collection of domain models includes a set curated by NCBI, which utilizes 3D structure to provide insights into sequence/structure/function relationships
<<<!!!<<< The page is no longer available. This database was already retired, and on this page users could find information on how to search and use these sequences. dbSTS was an NCBI resource that contained sequence data for short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. >>>!!!>>>
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Covalent DNA modifications have been found in numerous organisms and more are continually being discovered and characterized, as detection methods improve. Many of these modifications can affect the conformation of the DNA double helix, often resulting in downstream effects upon transcription factor binding. Some of these modifications have been demonstrated to be stable, while others are viewed as merely transient. DNAmod catalogues information on known DNA modifications, of which the well-known 5-methylcytosine is only one. It aims to profile modifications' properties, building upon data contained within the Chemical Entities of Biological Interest (ChEBI) database. It also provides literature citations and includes curated annotations on mapping techniques and natural occurrence information.
The goal of creating the Human Oral Microbiome Database (HOMD) is to provide the scientific community with comprehensive information o­n the approximately 700 prokaryote species that are present in the human oral cavity. Approximately 49% are officially named, 17% unnamed (but cultivated) and 34% are known o­nly as uncultivated phylotypes. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference scheme. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Genome sequences for oral bacteria determined as part of this project, the Human Microbiome Project, and other sequencing projects are being added to the HOMD as they become available. Genomes for 315 oral taxa (46% of taxa o­n HOMD) are currently available o­n HOMD. The HOMD site offers easy to use tools for viewing all publically available oral bacterial genomes.
The ENCODE Encyclopedia organizes the most salient analysis products into annotations, and provides tools to search and visualize them. The Encyclopedia has two levels of annotations: Integrative-level annotations integrate multiple types of experimental data and ground level annotations. Ground-level annotations are derived directly from the experimental data, typically produced by uniform processing pipelines.
Swiss Institute of Bioinformatics (SIB) coordinates research and education in bioinformatics throughout Switzerland and provides bioinformatics services to the national and international research community. ExPASy gives access to numerous repositories and databases of SIB. For example: array map, MetaNetX, SWISS-MODEL and World-2DPAGE, and many others see a list here http://www.expasy.org/resources
dbEST is a division of GenBank that contains sequence data and other information on "single-pass" cDNA sequences, or "Expressed Sequence Tags", from a number of organisms. Expressed Sequence Tags (ESTs) are short (usually about 300-500 bp), single-pass sequence reads from mRNA (cDNA). Typically they are produced in large batches. They represent a snapshot of genes expressed in a given tissue and/or at a given developmental stage. They are tags (some coding, others not) of expression for a given cDNA library. Most EST projects develop large numbers of sequences. These are commonly submitted to GenBank and dbEST as batches of dozens to thousands of entries, with a great deal of redundancy in the citation, submitter and library information. To improve the efficiency of the submission process for this type of data, we have designed a special streamlined submission process and data format. dbEST also includes sequences that are longer than the traditional ESTs, or are produced as single sequences or in small batches. Among these sequences are products of differential display experiments and RACE experiments. The thing that these sequences have in common with traditional ESTs, regardless of length, quality, or quantity, is that there is little information that can be annotated in the record. If a sequence is later characterized and annotated with biological features such as a coding region, 5'UTR, or 3'UTR, it should be submitted through the regular GenBank submissions procedure (via BankIt or Sequin), even if part of the sequence is already in dbEST. dbEST is reserved for single-pass reads. Assembled sequences should not be submitted to dbEST. GenBank will accept assembled EST submissions for the forthcoming TSA (Transcriptome Shotgun Assembly) division. The individual reads which make up the assembly should be submitted to dbEST, the Trace archive or the Short Read Archive (SRA) prior to the submission of the assemblies.
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<<<!!!<<< Genome data generated by BC Genome Sciences Centre is no longer available through this site as it is regularly deposited into controlled data repositories such as the European Genome Phenome Archive (EGA); ICGC (International Cancer Genome Consortium) and the Genome Data Commons (GDC) >>>!!!>>> Mapping, copy number analysis, sequence and gene expression data generated by the High Resolution Analysis of Follicular Lymphoma Genomes project. The data will be available for 24 patients with follicular lymphoma. All data will be made as widely and freely available as possible while safeguarding the privacy of participants, and protecting confidential and proprietary data.The data from this project will be submitted to public genomic data sources. These sources will be listed on this web site as the data becomes available in these external data sources.
The Fungal Genetics Stock Center has preserved and distributed strains of genetically characterized fungi since 1960. The collection includes over 20,000 accessioned strains of classical and genetically engineered mutants of key model, human, and plant pathogenic fungi. These materials are distributed as living stocks to researchers around the world.
The Fragile Families and Child Wellbeing Study changed its name to The Future of Families and Child Wellbeing Study (FFCWS). Note that all documentation issued prior to January 2023 contains the study’s former name. Any further reference to FFCWS should kindly observe this name change. The Fragile Families & Child Wellbeing Study is following a cohort of nearly 5,000 children born in large U.S. cities between 1998 and 2000 (roughly three-quarters of whom were born to unmarried parents). We refer to unmarried parents and their children as “fragile families” to underscore that they are families and that they are at greater risk of breaking up and living in poverty than more traditional families. The core Study was originally designed to primarily address four questions of great interest to researchers and policy makers: (1) What are the conditions and capabilities of unmarried parents, especially fathers?; (2) What is the nature of the relationships between unmarried parents?; (3) How do children born into these families fare?; and (4) How do policies and environmental conditions affect families and children?