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Found 126 result(s)
Clinical Genomic Database (CGD) is a manually curated database of conditions with known genetic causes, focusing on medically significant genetic data with available interventions.
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<<<!!!<<< This repository is no longer available. >>>!!!>>> Message since 2018-06: This virtual host is being reconstructed.
Open access to macromolecular X-ray diffraction and MicroED datasets. The repository complements the Worldwide Protein Data Bank. SBDG also hosts reference collection of biomedical datasets contributed by members of SBGrid, Harvard and pilot communities.
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Oral Cancer Gene Database is an initiative of the Advanced Centre for Treatment, Research and Education in Cancer, Navi Mumbai. The present database, version II, consists of 374 genes. It is developed as a user friendly site that would provide the scientist, information and external links from one place. The database is accessed through a list of all genes, and Keyword Search using gene name or gene symbol, chromosomal location, CGH (in %), and molecular weight. Interaction Network shows the interaction between genes for particular biological processes and molecular functions.
This library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The Cell Image Library has been merged with "Cell Centered Database" in 2017. The purpose of the database is to advance research on cellular activity, with the ultimate goal of improving human health.
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The DrugBank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information. The latest release of DrugBank (version 5.1.1, released 2018-07-03) contains 11,881 drug entries including 2,526 approved small molecule drugs, 1,184 approved biotech (protein/peptide) drugs, 129 nutraceuticals and over 5,751 experimental drugs. Additionally, 5,132 non-redundant protein (i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries. Each DrugCard entry contains more than 200 data fields with half of the information being devoted to drug/chemical data and the other half devoted to drug target or protein data.
<<<!!!<<< As of June 30, 2017, HardinMD has been retired, although it is still findable through the WayBack Machine >>>!!!>>>
Candida Genome Database, a resource for genomic sequence data and gene and protein information for Candida albicans and related species. CGD is based on the Saccharomyces Genome Database. The Candida Genome Database (CGD) provides online access to genomic sequence data and manually curated functional information about genes and proteins of the human pathogen Candida albicans and related species. C. albicans is the best studied of the human fungal pathogens. It is a common commensal organism of healthy individuals, but can cause debilitating mucosal infections and life-threatening systemic infections, especially in immunocompromised patients. C. albicans also serves as a model organism for the study of other fungal pathogens.
Neuroimaging Tools and Resources Collaboratory (NITRC) is currently a free one-stop-shop environment for science researchers that need resources such as neuroimaging analysis software, publicly available data sets, and computing power. Since its debut in 2007, NITRC has helped the neuroscience community to use software and data produced from research that, before NITRC, was routinely lost or disregarded, to make further discoveries. NITRC provides free access to data and enables pay-per-use cloud-based access to unlimited computing power, enabling worldwide scientific collaboration with minimal startup and cost. With NITRC and its components—the Resources Registry (NITRC-R), Image Repository (NITRC-IR), and Computational Environment (NITRC-CE)—a researcher can obtain pilot or proof-of-concept data to validate a hypothesis for a few dollars.
Gemma is a database for the meta-analysis, re-use and sharing of genomics data, currently primarily targeted at the analysis of gene expression profiles. Gemma contains data from thousands of public studies, referencing thousands of published papers. Users can search, access and visualize co-expression and differential expression results.
M-CSA is a database of enzyme reaction mechanisms. It provides annotation on the protein, catalytic residues, cofactors, and the reaction mechanisms of hundreds of enzymes. There are two kinds of entries in M-CSA. 'Detailed mechanism' entries are more complete and show the individual chemical steps of the mechanism as schemes with electron flow arrows. 'Catalytic Site' entries annotate the catalytic residues necessary for the reaction, but do not show the mechanism. The M-CSA (Mechanism and Catalytic Site Atlas) represents a unified resource that combines the data in both MACiE and the CSA
TRAILS is a prospective cohort study, which started in 2001 with population cohort and 2004 with a clinical cohort (CC). Since then, a group of 2500 young people from the Northern part of the Netherlands has been closely monitored in order to chart and explain their mental, physical, and social development. These TRAILS participants have been measured every two to three years, by means of questionnaires, interviews, and all kinds of tests. By now, we have collected information that spans the total period from preadolescence up until young adulthood. One of the main goals of TRAILS is to contribute to the knowledge of the development of emotional and behavioral problems and the (social) functioning of preadolescents into adulthood, their determinants, and underlying mechanisms.
STOREDB is a platform for the archiving and sharing of primary data and outputs of all kinds, including epidemiological and experimental data, from research on the effects of radiation. It also provides a directory of bioresources and databases containing information and materials that investigators are willing to share. STORE supports the creation of a radiation research commons.
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?
Project Achilles is a systematic effort aimed at identifying and cataloging genetic vulnerabilities across hundreds of genomically characterized cancer cell lines. The project uses genome-wide genetic perturbation reagents (shRNAs or Cas9/sgRNAs) to silence or knock-out individual genes and identify those genes that affect cell survival. Large-scale functional screening of cancer cell lines provides a complementary approach to those studies that aim to characterize the molecular alterations (e.g. mutations, copy number alterations) of primary tumors, such as The Cancer Genome Atlas (TCGA). The overall goal of the project is to identify cancer genetic dependencies and link them to molecular characteristics in order to prioritize targets for therapeutic development and identify the patient population that might benefit from such targets. Project Achilles data is hosted on the Cancer Dependency Map Portal (DepMap) where it has been harmonized with our genomics and cellular models data. You can access the latest and all past datasets here: https://depmap.org/portal/download/all/
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During cell cycle, numerous proteins temporally and spatially localized in distinct sub-cellular regions including centrosome (spindle pole in budding yeast), kinetochore/centromere, cleavage furrow/midbody (related or homolog structures in plants and budding yeast called as phragmoplast and bud neck, respectively), telomere and spindle spatially and temporally. These sub-cellular regions play important roles in various biological processes. In this work, we have collected all proteins identified to be localized on kinetochore, centrosome, midbody, telomere and spindle from two fungi (S. cerevisiae and S. pombe) and five animals, including C. elegans, D. melanogaster, X. laevis, M. musculus and H. sapiens based on the rationale of "Seeing is believing" (Bloom K et al., 2005). Through ortholog searches, the proteins potentially localized at these sub-cellular regions were detected in 144 eukaryotes. Then the integrated and searchable database MiCroKiTS - Midbody, Centrosome, Kinetochore, Telomere and Spindle has been established.
The Twenty-07 Study was set up in 1986 in order to investigate the reasons for differences in health by socio-economic circumstances, gender, area of residence, age, ethnic group, and family type. 4510 people are being followed for 20 years. The initial wave of data collection took place in 1987/8, when respondents were aged 15, 35 and 55. The final wave of data collection took place in 2007/08 when respondents were aged 35, 55 and 75. In this way the Twenty-07 Study provides us with unique opportunities to investigate both the changes in people's lives over 20 years and how they affect their health, and the differences in people's experiences at the same ages 20 years apart, and how these have different effects on their health.
<<<!!!<<< OFFLINE >>>!!!>>> A recent computer security audit has revealed security flaws in the legacy HapMap site that require NCBI to take it down immediately. We regret the inconvenience, but we are required to do this. That said, NCBI was planning to decommission this site in the near future anyway (although not quite so suddenly), as the 1,000 genomes (1KG) project has established itself as a research standard for population genetics and genomics. NCBI has observed a decline in usage of the HapMap dataset and website with its available resources over the past five years and it has come to the end of its useful life. The International HapMap Project is a multi-country effort to identify and catalog genetic similarities and differences in human beings. Using the information in the HapMap, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. The Project is a collaboration among scientists and funding agencies from Japan, the United Kingdom, Canada, China, Nigeria, and the United States. All of the information generated by the Project will be released into the public domain. The goal of the International HapMap Project is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. By making this information freely available, the Project will help biomedical researchers find genes involved in disease and responses to therapeutic drugs. In the initial phase of the Project, genetic data are being gathered from four populations with African, Asian, and European ancestry. Ongoing interactions with members of these populations are addressing potential ethical issues and providing valuable experience in conducting research with identified populations. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. The Project officially started with a meeting in October 2002 (https://www.genome.gov/10005336/) and is expected to take about three years.
CPES provides access to information that relates to mental disorders among the general population. Its primary goal is to collect data about the prevalence of mental disorders and their treatments in adult populations in the United States. It also allows for research related to cultural and ethnic influences on mental health. CPES combines the data collected in three different nationally representative surveys (National Comorbidity Survey Replication, National Survey of American Life, National Latino and Asian American Study).