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Found 68 result(s)
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Indian Genetic Disease Database (IGDD) is an initiative of CSIR Indian Institute of Chemical Biology. It is supported by Council of Scientific and Industrial Research (CSIR) and Department of Biotechnology (DBT) of India. The Indian people represent one-sixth of the world population and consists of a ethnically, geographically, and genetically diverse population. In some communities the ratio of genetic disorder is relatively high due to consanguineous marriage practiced in the community. This database has been created to keep track of mutations in the causal genes for genetic diseases common in India and help the physicians, geneticists, and other professionals retrieve and use the information for the benefit of the public. The database includes scientific information about these genetic diseases and disabilities, but also statistical information about these diseases in today's society. Data is categorized by body part affected and then by title of the disease.
Clone DB contains information about genomic clones and cDNA and cell-based libraries for eukaryotic organisms. The database integrates this information with sequence data, map positions, and distributor information. At this time, Clone DB contains records for genomic clones and libraries, the collection of MICER mouse gene targeting clones and cell-based gene trap and gene targeting libraries from the International Knockout Mouse Consortium, Lexicon and the International Gene Trap Consortium. A planned expansion for Clone DB will add records for additional gene targeting and gene trap clones, as well as cDNA clones.
Intrepid Bioinformatics serves as a community for genetic researchers and scientific programmers who need to achieve meaningful use of their genetic research data – but can’t spend tremendous amounts of time or money in the process. The Intrepid Bioinformatics system automates time consuming manual processes, shortens workflow, and eliminates the threat of lost data in a faster, cheaper, and better environment than existing solutions. The system also provides the functionality and community features needed to analyze the large volumes of Next Generation Sequencing and Single Nucleotide Polymorphism data, which is generated for a wide range of purposes from disease tracking and animal breeding to medical diagnosis and treatment.
The objective of this Research Coordination Network project is to develop an international network of researchers who use genetic methodologies to study the ecology and evolution of marine organisms in the Indo-Pacific to share data, ideas and methods. The tropical Indian and Pacific Oceans encompass the largest biogeographic region on the planet, the Indo-Pacific
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The Autism Chromosome Rearrangement Database is a collection of hand curated breakpoints and other genomic features, related to autism, taken from publicly available literature: databases and unpublished data. The database is continuously updated with information from in-house experimental data as well as data from published research studies.
GESDB is a platform for sharing simulation data and discussion of simulation techniques for human genetic studies. The database contains simulation scripts, simulated data, and documentations from published manuscripts. The forum provides a platform for Q&A for the simulated data and exchanging simulation ideas. GESDB aims to promote transparency and efficiency in simulation studies for human genetic studies.
Edinburgh DataShare is an online digital repository of multi-disciplinary research datasets produced at the University of Edinburgh, hosted by the Data Library in Information Services. Edinburgh University researchers who have produced research data associated with an existing or forthcoming publication, or which has potential use for other researchers, are invited to upload their dataset for sharing and safekeeping. A persistent identifier and suggested citation will be provided.
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. OMIM is authored and edited at the McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, under the direction of Dr. Ada Hamosh. Its official home is omim.org.
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CBS offers Comprehensive public databases of DNA- and protein sequences, macromolecular structure, g ene and protein expression levels, pathway organization and cell signalling, have been established to optimise scientific exploitation of the explosion of data within biology. Unlike many other groups in the field of biomolecular informatics, Center for Biological Sequence Analysis directs its research primarily towards topics related to the elucidation of the functional aspects of complex biological mechanisms. Among contemporary bioinformatics concerns are reliable computational interpretation of a wide range of experimental data, and the detailed understanding of the molecular apparatus behind cellular mechanisms of sequence information. By exploiting available experimental data and evidence in the design of algorithms, sequence correlations and other features of biological significance can be inferred. In addition to the computational research the center also has experimental efforts in gene expression analysis using DNA chips and data generation in relation to the physical and structural properties of DNA. In the last decade, the Center for Biological Sequence Analysis has produced a large number of computational methods, which are offered to others via WWW servers.
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 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 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.
Probe database provides a public registry of nucleic acid reagents as well as information on reagent distributors, sequence similarities and probe effectiveness. Database users have access to applications of gene expression, gene silencing and mapping, as well as reagent variation analysis and projects based on probe-generated data. The Probe database is constantly updated.
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 dbMHC database provides an open, publicly accessible platform for DNA and clinical data related to the human Major Histocompatibility Complex (MHC). The dbMHC provides access to human leukocyte antigen (HLA) sequences, HLA allele and haplotype frequencies, and clinical datasets.
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.
The NCI's Genomic Data Commons (GDC) provides the cancer research community with a unified data repository that enables data sharing across cancer genomic studies in support of precision medicine. The GDC obtains validated datasets from NCI programs in which the strategies for tissue collection couples quantity with high quality. Tools are provided to guide data submissions by researchers and institutions.
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One of the world’s largest banks of biological, psychosocial and clinical data on people suffering from mental health problems. The Signature center systematically collects biological, psychosocial and clinical indicators from patients admitted to the psychiatric emergency and at four points throughout their journey in the hospital: upon arrival to the emergency room (state of crisis), at the end of their hospital stay, as well as at the beginning and the end of outpatient treatment. For all hospital clients who agree to participate, blood specimens are collected for the purpose of measuring metabolic, genetic, toxic and infectious biomarkers, while saliva samples are collected to measure sex hormones and hair samples are collected to measure stress hormones. Questionnaire has been selected to cover important dimensional aspects of mental illness such as Behaviour and Cognition (Psychosis, Depression, Anxiety, Impulsiveness, Aggression, Suicide, Addiction, Sleep),Socio-demographic Profile (Spiritual beliefs, Social functioning, Childhood experiences, Demographic, Family background) and Medical Data (Medication, Diagnosis, Long-term health, RAMQ data). On 2016, May there are more than 1150 participants and 400 for the longitudinal Follow-Up
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.
The CCDB project was started in 1998 under the auspices of the Human Brain Project to provide a venue for sharing and mining cellular and subcellular data derived from light and electron microscopy, including correlated imaging. It was one of the first web databases devoted to the then emerging technique of electron tomography. The CCDB has been on-line since 2002.
In 2003, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) at NIH established Data, Biosample, and Genetic Repositories to increase the impact of current and previously funded NIDDK studies by making their data and biospecimens available to the broader scientific community. These Repositories enable scientists not involved in the original study to test new hypotheses without any new data or biospecimen collection, and they provide the opportunity to pool data across several studies to increase the power of statistical analyses. In addition, most NIDDK-funded studies are collecting genetic biospecimens and carrying out high-throughput genotyping making it possible for other scientists to use Repository resources to match genotypes to phenotypes and to perform informative genetic analyses.
The Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, genetic information and health care expenditures.
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?