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Found 74 result(s)
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Human biomaterial banks (short: biobanks) are collections of human body substances (i.e. blood, DNA, urine or tissue) connected with disease specific information. This allow for research of relations between deseases and underlying (molecular) modifications and paves the way for developing target-oriented therapies ("personalized medicine"). The biobank material arises from samples taken for therapeutical or diagnostic reasons or is extracted in the context of clinical trials. An approval for usage by the patient is always needed prior to any research activities.
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The RAMEDIS system is a platform independent, web-based information system for rare metabolic diseases based on filed case reports. It was developed in close cooperation with clinical partners to allow them to collect information on rare metabolic diseases with extensive details, e.g. about occurring symptoms, laboratory findings, therapy and molecular data.
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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.
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.
METLIN represents the largest MS/MS collection of data with the database generated at multiple collision energies and in positive and negative ionization modes. The data is generated on multiple instrument types including SCIEX, Agilent, Bruker and Waters QTOF mass spectrometers.
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 Brain Biodiversity Bank refers to the repository of images of and information about brain specimens contained in the collections associated with the National Museum of Health and Medicine at the Armed Forces Institute of Pathology in Washington, DC. These collections include, besides the Michigan State University Collection, the Welker Collection from the University of Wisconsin, the Yakovlev-Haleem Collection from Harvard University, the Meyer Collection from the Johns Hopkins University, and the Huber-Crosby and Crosby-Lauer Collections from the University of Michigan and the C.U. Ariëns Kappers brain collection from Amsterdam Netherlands.Introducing online atlases of the brains of humans, sheep, dolphins, and other animals. A world resource for illustrations of whole brains and stained sections from a great variety of mammals
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.
INDEPTH is a global network of research centres that conduct longitudinal health and demographic evaluation of populations in low- and middle-income countries (LMICs). INDEPTH aims to strengthen global capacity for Health and Demographic Surveillance Systems (HDSSs), and to mount multi-site research to guide health priorities and policies in LMICs, based on up-to-date scientific evidence. The data collected by the INDEPTH Network members constitute a valuable resource of population and health data for LMIC countries. This repository aims to make well documented anonymised longitudinal microdata from these Centres available to data users.
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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.
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<<<!!!<<< This product is in the archive and is no longer current. >>>!!!>>> Biobanks are a key prerequisite for modern medical research. By linking samples and clinical data they make it possible to clarify the causes and the course of diseases. The German Biobank Registry pools the medically relevant biobanks in Germany. The German Biobank Registry provides an overview of the medical biobanks in Germany; increases the international visibility of German biobanks; facilitates the networking of biobanks; promotes an exchange of information and samples between research teams; supports the use of existing resources; provides information for investments in biobanks and promotes transparency and trust in research where human samples are used. Searching for samples in all biobanks is possible at the project portal (P2B2) https://p2b2.fraunhofer.de/ after registration.
The Brain Transcriptome Database (BrainTx) project aims to create an integrated platform to visualize and analyze our original transcriptome data and publicly accessible transcriptome data related to the genetics that underlie the development, function, and dysfunction stages and states of the brain.
!!! >>> the repository is offline >>> !!! GOBASE is a taxonomically broad organelle genome database that organizes and integrates diverse data related to mitochondria and chloroplasts. GOBASE is currently expanding to include information on representative bacteria that are thought to be specifically related to the bacterial ancestors of mitochondria and chloroplasts
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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.
This interface provides access to several types of data related to the Chesapeake Bay. Bay Program databases can be queried based upon user-defined inputs such as geographic region and date range. Each query results in a downloadable, tab- or comma-delimited text file that can be imported to any program (e.g., SAS, Excel, Access) for further analysis. Comments regarding the interface are encouraged. Questions in reference to the data should be addressed to the contact provided on subsequent pages.
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.
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<<<!!!<<< 2017-06-02: We recently suffered a server failure and are working to bring the full ORegAnno website back online. In the meantime, you may download the complete database here: http://www.oreganno.org/dump/ ; Data are also available through UCSC Genome Browser (e.g., hg38 -> Regulation -> ORegAnno) https://genome.ucsc.edu/cgi-bin/hgTrackUi?hgsid=686342163_2it3aVMQVoXWn0wuCjkNOVX39wxy&c=chr1&g=oreganno >>>!!!>>> The Open REGulatory ANNOtation database (ORegAnno) is an open database for the curation of known regulatory elements from scientific literature. Annotation is collected from users worldwide for various biological assays and is automatically cross-referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, the eVOC: Cell type ontology, and the Taxonomy database, where appropriate, with information regarding the original experimentation performed (evidence). ORegAnno further provides an open validation process for all regulatory annotation in the public domain. Assigned validators receive notification of new records in the database and are able to cross-reference the citation to ensure record integrity. Validators have the ability to modify any record (deprecating the old record and creating a new one) if an error is found. Further, any contributor to the database can comment on any annotation by marking errors, or adding special reports into function as they see fit. These features of ORegAnno ensure that the collection is of the highest quality and uniquely provides a dynamic view of our changing understanding of gene regulation in the various genomes.