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Found 36 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.
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Data Download section provides easy access to the ABMI’s data and innovative data products ranging from raw field data, to species habitat associations, to remote sensing and geospatial products, to animal camera trap data, and more.
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.
The goals of the Drosophila Genome Center are to finish the sequence of the euchromatic genome of Drosophila melanogaster to high quality and to generate and maintain biological annotations of this sequence. In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community.
In early 2010 we updated the site to facilitate more rapid transfer of our data to the public database and focus our efforts on the core mission of providing expression pattern images to the research community. The original database https://www.fruitfly.org/index.html reproduced functions available on FlyBase, complicating our updates by the requirement to re-synchronize with FlyBase updates. Our expression reports on the new site still link to FlyBase gene reports, but we no longer reproduce FlyBase functions and therefore can update expression data on an ongoing basis instead of more infrequent major releases. All the functions relating to the expression patterns remain and we soon will add an option to search expression patterns by image similarity, in addition to annotation term searches. In a transitional phase we will leave both the old and the new sites up, but the newer data (post Release 2) will appear only on the new website. We welcome any feedback or requests for additional features. - The goals of the Drosophila Genome Center are to finish the sequence of the euchromatic genome of Drosophila melanogaster to high quality and to generate and maintain biological annotations of this sequence. In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community.
The datacommons@psu was developed in 2005 to provide a resource for data sharing, discovery, and archiving for the Penn State research and teaching community. Access to information is vital to the research, teaching, and outreach conducted at Penn State. The datacommons@psu serves as a data discovery tool, a data archive for research data created by PSU for projects funded by agencies like the National Science Foundation, as well as a portal to data, applications, and resources throughout the university. The datacommons@psu facilitates interdisciplinary cooperation and collaboration by connecting people and resources and by: Acquiring, storing, documenting, and providing discovery tools for Penn State based research data, final reports, instruments, models and applications. Highlighting existing resources developed or housed by Penn State. Supporting access to project/program partners via collaborative map or web services. Providing metadata development citation information, Digital Object Identifiers (DOIs) and links to related publications and project websites. Members of the Penn State research community and their affiliates can easily share and house their data through the datacommons@psu. The datacommons@psu will also develop metadata for your data and provide information to support your NSF, NIH, or other agency data management plan.
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.
The Ensembl project produces genome databases for vertebrates and other eukaryotic species. Ensembl is a joint project between the European Bioinformatics Institute (EBI) and the Wellcome Trust Sanger Institute (WTSI) to develop a software system that produces and maintains automatic annotation on selected genomes.The Ensembl project was started in 1999, some years before the draft human genome was completed. Even at that early stage it was clear that manual annotation of 3 billion base pairs of sequence would not be able to offer researchers timely access to the latest data. The goal of Ensembl was therefore to automatically annotate the genome, integrate this annotation with other available biological data and make all this publicly available via the web. Since the website's launch in July 2000, many more genomes have been added to Ensembl and the range of available data has also expanded to include comparative genomics, variation and regulatory data. Ensembl is a joint project between European Bioinformatics Institute (EBI), an outstation of the European Molecular Biology Laboratory (EMBL), and the Wellcome Trust Sanger Institute (WTSI). Both institutes are located on the Wellcome Trust Genome Campus in Hinxton, south of the city of Cambridge, United Kingdom.
The Ensembl genome annotation system, developed jointly by the EBI and the Wellcome Trust Sanger Institute, has been used for the annotation, analysis and display of vertebrate genomes since 2000. Since 2009, the Ensembl site has been complemented by the creation of five new sites, for bacteria, protists, fungi, plants and invertebrate metazoa, enabling users to use a single collection of (interactive and programatic) interfaces for accessing and comparing genome-scale data from species of scientific interest from across the taxonomy. In each domain, we aim to bring the integrative power of Ensembl tools for comparative analysis, data mining and visualisation across genomes of scientific interest, working in collaboration with scientific communities to improve and deepen genome annotation and interpretation.
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.
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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GSA is a data repository specialized for archiving raw sequence reads. It supports data generated from a variety of sequencing platforms ranging from Sanger sequencing machines to single-cell sequencing machines and provides data storing and sharing services free of charge for worldwide scientific communities. In addition to raw sequencing data, GSA also accommodates secondary analyzed files in acceptable formats (like BAM, VCF). Its user-friendly web interfaces simplify data entry and submitted data are roughly organized as two parts, viz., Metadata and File, where the former can be further assorted into BioProject, BioSample, Experiment and Run, and the latter contains raw sequence reads.
GermOnline 4.0 is a cross-species database gateway focusing on high-throughput expression data relevant for germline development, the meiotic cell cycle and mitosis in healthy versus malignant cells. The portal provides access to the Saccharomyces Genomics Viewer (SGV) which facilitates online interpretation of complex data from experiments with high-density oligonucleotide tiling microarrays that cover the entire yeast genome.
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iDog, an integrated resource for domestic dog (Canis lupus familiaris) and wild canids, provides the worldwide dog research community a variety of data services. This includes Genes, Genomes, SNPs, Breed/Disease Traits, Gene Expressions, Single Cell, Dog-Human Homolog Diseases and Literatures. In addition, iDog provides Online tools for performing genomic data visualization and analyses.
The IMPC is a confederation of international mouse phenotyping projects working towards the agreed goals of the consortium: To undertake the phenotyping of 20,000 mouse mutants over a ten year period, providing the first functional annotation of a mammalian genome. Maintain and expand a world-wide consortium of institutions with capacity and expertise to produce germ line transmission of targeted knockout mutations in embryonic stem cells for 20,000 known and predicted mouse genes. Test each mutant mouse line through a broad based primary phenotyping pipeline in all the major adult organ systems and most areas of major human disease. Through this activity and employing data annotation tools, systematically aim to discover and ascribe biological function to each gene, driving new ideas and underpinning future research into biological systems; Maintain and expand collaborative “networks” with specialist phenotyping consortia or laboratories, providing standardized secondary level phenotyping that enriches the primary dataset, and end-user, project specific tertiary level phenotyping that adds value to the mammalian gene functional annotation and fosters hypothesis driven research; and Provide a centralized data centre and portal for free, unrestricted access to primary and secondary data by the scientific community, promoting sharing of data, genotype-phenotype annotation, standard operating protocols, and the development of open source data analysis tools. Members of the IMPC may include research centers, funding organizations and corporations.
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. The projects contributing to this resource are: Mouse Genome Database (MGD) Project, Gene Expression Database (GXD) Project, Mouse Tumor Biology (MTB) Database Project, Gene Ontology (GO) Project at MGI, MouseMine Project, MouseCyc Project at MGI
The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary cancer by providing electronic access to: Information on endogenous spontaneous and induced tumors in mice, including tumor frequency & latency data, Information on genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice) in which tumors arise, Information on genetic factors associated with tumor susceptibility in mice and somatic genetic-mutations observed in the tumors, Tumor pathology reports and images, References, supporting MTB data and Links to other online resources for cancer.
<<<!!!<<< NCBI announced plans to retire the Clone DB web interface. Pursuant to this retirement, starting on May 27, 2019, all web pages associated with Clone DB and CloneFinder will redirect to this blog post https://ncbiinsights.ncbi.nlm.nih.gov/?s=clone+db. Links to Clone DB from the NCBI home page will also be going away. >>>!!!>>>
The dbVar is a database of genomic structural variation containing data from multiple gene studies. Users can browse data containing the number of variant cells from each study, and filter studies by organism, study type, method and genomic variant. Organisms include human, mouse, cattle and several additional animals. ***NCBI will phase out support for non-human organism data in dbSNP and dbVar beginning on September 1, 2017 ***
The Gene database provides detailed information for known and predicted genes defined by nucleotide sequence or map position. Gene supplies gene-specific connections in the nexus of map, sequence, expression, structure, function, citation, and homology data. Unique identifiers are assigned to genes with defining sequences, genes with known map positions, and genes inferred from phenotypic information. These gene identifiers are used throughout NCBI's databases and tracked through updates of annotation. Gene includes genomes represented by NCBI Reference Sequences (or RefSeqs) and is integrated for indexing and query and retrieval from NCBI's Entrez and E-Utilities systems.
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.
The Entrez Protein Clusters database contains annotation information, publications, structures and analysis tools for related protein sequences encoded by complete genomes. The data available in the Protein Clusters Database is generated from prokaryotic genomic studies and is intended to assist researchers studying micro-organism evolution as well as other biological sciences. Available genomes include plants and viruses as well as organelles and microbial genomes.
The Structure database provides three-dimensional structures of macromolecules for a variety of research purposes and allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships.