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Found 69 result(s)
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>>>!!!<<< The repository is no longer available. >>>!!!<<< 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.
!!! >>> intrepidbio.com expired <<< !!!! 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.
DNASU is a central repository for plasmid clones and collections. Currently we store and distribute over 200,000 plasmids including 75,000 human and mouse plasmids, full genome collections, the protein expression plasmids from the Protein Structure Initiative as the PSI: Biology Material Repository (PSI : Biology-MR), and both small and large collections from individual researchers. We are also a founding member and distributor of the ORFeome Collaboration plasmid collection.
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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.
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The JenAge Ageing Factor Database AgeFactDB is aimed at the collection and integration of ageing phenotype and lifespan data. Ageing factors are genes, chemical compounds or other factors such as dietary restriction, for example. In a first step ageing-related data are primarily taken from existing databases. In addition, new ageing-related information is included both by manual and automatic information extraction from the scientific literature. Based on a homology analysis, AgeFactDB also includes genes that are homologous to known ageing-related genes. These homologs are considered as candidate or putative ageing-related genes.
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NODE (The National Omics Data Encyclopedia) provides an integrated, compatible, comparable, and scalable multi-omics resource platform that supports flexible data management and effective data release. NODE uses a hierarchical data architecture to support storage of muti-omics data including sequencing data, MS based proteomics data, MS or NMR based metabolomics data, and fluorescence imaging data. Launched in early 2017, NODE has collected and published over 900 terabytes of omics data for researchers from China and all over the world in last three years, 22% of which contains multiple omics data. NODE provides functions around the whole life cycle of omics data, from data archive, data requests/responses to data sharing, data analysis, data review and publish.
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.
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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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
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.
NCBI Datasets is a continually evolving platform designed to provide easy and intuitive access to NCBI’s sequence data and metadata. NCBI Datasets is part of the NIH Comparative Genomics Resource (CGR). CGR facilitates reliable comparative genomics analyses for all eukaryotic organisms through an NCBI Toolkit and community collaboration.
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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 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.
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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.
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.
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 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?
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
CODEX is a database of NGS mouse and human experiments. Although, the main focus of CODEX is Haematopoiesis and Embryonic systems, the database includes a large variety of cell types. In addition to the publically available data, CODEX also includes a private site hosting non-published data. CODEX provides access to processed and curated NGS experiments. To use CODEX: (i) select a specialized repository (HAEMCODE or ESCODE) or choose the whole compendium (CODEX), then (ii) filter by organism and (iii) choose how to explore the database.
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The Cystic Fibrosis Mutation Database (CFTR1) was initiated by the Cystic Fibrosis Genetic Analysis Consortium in 1989 to increase and facilitate communications among CF researchers, and is maintained by the Cystic Fibrosis Centre at the Hospital for Sick Children in Toronto. The specific aim of the database is to provide up to date information about individual mutations in the CFTR gene. In a major upgrade in 2010, all known CFTR mutations and sequence variants have been converted to the standard nomenclature recommended by the Human Genome Variation Society.
The Bacterial and Viral Bioinformatics Resource Center (BV-BRC) is an information system designed to support research on bacterial and viral infectious diseases. BV-BRC combines two long-running BRCs: PATRIC, the bacterial system, and IRD/ViPR, the viral systems.
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.
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.