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Found 336 result(s)
The Scholarly Database (SDB) at Indiana University aims to serve researchers and practitioners interested in the analysis, modeling, and visualization of large-scale scholarly datasets. The online interface provides access to six datasets: MEDLINE papers, registered Clinical Trials, U.S. Patent and Trademark Office patents (USPTO), National Science Foundation (NSF) funding, National Institutes of Health (NIH) funding, and National Endowment for the Humanities funding – over 26 million records in total.
As a department of the United States Department of Agriculture (USDA) the National Agricultural Statistics Service (NASS) continually surveys and reports on U.S. agriculture. NASS reports include production and supplies of food and fiber, prices paid and received by farmers, farm labor and wages, farm finances, chemical use, and changes in the demographics of U.S. producers. NASS provides objective and unbiased statistics of states and counties, while safeguarding the privacy of farmers and ranchers.
Online Mendelian Inheritance in Animals (OMIA) is a catalogue/compendium of inherited disorders, other (single-locus) traits, and genes in 218 animal species (other than human and mouse and rats, which have their own resources) authored by Professor Frank Nicholas of the University of Sydney, Australia, with help from many people over the years. OMIA information is stored in a database that contains textual information and references, as well as links to relevant PubMed and Gene records at the NCBI, and to OMIM and Ensembl.
>>>!!!<<< SMD has been retired. After approximately fifteen years of microarray-centric research service, the Stanford Microarray Database has been retired. We apologize for any inconvenience; please read below for possible resolutions to your queries. If you are looking for any raw data that was directly linked to SMD from a manuscript, please search one of the public repositories. NCBI Gene Expression Omnibus EBI ArrayExpress All published data were previously communicated to one (or both) of the public repositories. Alternatively, data for publications between 1997 and 2004 were likely migrated to the Princeton University MicroArray Database, and are accessible there. If you are looking for a manuscript supplement (i.e. from a domain other than smd.stanford.edu), perhaps try searching the Internet Archive: Wayback Machine https://archive.org/web/ . >>>!!!<<< The Stanford Microarray Database (SMD) is a DNA microarray research database that provides a large amount of data for public use.
caNanoLab is a data sharing portal designed to facilitate information sharing in the biomedical nanotechnology research community to expedite and validate the use of nanotechnology in biomedicine. caNanoLab provides support for the annotation of nanomaterials with characterizations resulting from physico-chemical and in vitro assays and the sharing of these characterizations and associated nanotechnology protocols in a secure fashion.
Pubchem contains 3 databases. 1. PubChem BioAssay: The PubChem BioAssay Database contains bioactivity screens of chemical substances described in PubChem Substance. It provides searchable descriptions of each bioassay, including descriptions of the conditions and readouts specific to that screening procedure. 2. PubChem Compound: The PubChem Compound Database contains validated chemical depiction information provided to describe substances in PubChem Substance. Structures stored within PubChem Compounds are pre-clustered and cross-referenced by identity and similarity groups. 3. PubChem Substance. The PubChem Substance Database contains descriptions of samples, from a variety of sources, and links to biological screening results that are available in PubChem BioAssay. If the chemical contents of a sample are known, the description includes links to PubChem Compound.
The GHDx is our user-friendly and searchable data catalog for global health, demographic, and other health-related datasets. It provides detailed information about datasets ranging from censuses and surveys to health records and vital statistics, globally. It also serves as a platform for data owners to share their data with the public. The GDB Compare visualization, which allows the user to see rate of change in disease incidence, globally or by country, by age or across all ages, is especially powerful as a tool. Be sure to try adding a bottom chart, like the map, to augment the treemap that loads by default in the top chart.
>>>!!!<<< The repository is no longer available. >>>!!!<<< The eagle-i National Network and eagle-i resource search at www.eagle-.net was retired on November 4, 2021.!!! Groundbreaking biomedical research requires access to cutting edge scientific resources; however such resources are often invisible beyond the laboratories or universities where they were developed. eagle-i is a discovery platform that helps biomedical scientists find previously invisible, but highly valuable, resources.
The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
HPIDB is a public resource, which integrates experimental PPIs from various databases into a single database. The Host-Pathogen Interaction Database (HPIDB) is a genomics resource devoted to understanding molecular interactions between key organisms and the pathogens to which they are susceptible.
The Arizona State University (ASU) Research Data Repository provides a platform for ASU-affiliated researchers to share, preserve, cite, and make research data accessible and discoverable. The ASU Research Data Repository provides a permanent digital identifier for research data, which complies with data sharing policies. The repository is powered by the Dataverse open-source application, developed and used by Harvard University. Both the ASU Research Data Repository and the KEEP Institutional Repository are managed by the ASU Library to ensure research produced at Arizona State University is discoverable and accessible to the global community.
OBIS strives to document the ocean's diversity, distribution and abundance of life. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme
The Health and Medical Care Archive (HMCA) is the data archive of the Robert Wood Johnson Foundation (RWJF), the largest philanthropy devoted exclusively to health and health care in the United States. Operated by the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan, HMCA preserves and disseminates data collected by selected research projects funded by the Foundation and facilitates secondary analyses of the data. Our goal is to increase understanding of health and health care in the United States through secondary analysis of RWJF-supported data collections
Academic Commons provides open, persistent access to the scholarship produced by researchers at Columbia University, Barnard College, Jewish Theological Seminary, Teachers College, and Union Theological Seminary. Academic Commons is a program of the Columbia University Libraries. Academic Commons accepts articles, dissertations, research data, presentations, working papers, videos, and more.
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.
The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web. The JGI Genome Portal provides a unified access point to all JGI genomic databases and analytical tools. A user can find all DOE JGI sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. Databases: Genome Online Database (GOLD), Integrated Microbial Genomes (IGM), MycoCosm, Phytozome
The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans. BioGRID is an online interaction repository with data compiled through comprehensive curation efforts. All interaction data are freely provided through our search index and available via download in a wide variety of standardized formats.
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.
A community platform to Share Data, Publish Data with a DOI, and get Citations. Advancing Spinal Cord Injury research through sharing of data from basic and clinical research.
OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. So it serves as an important utility for automated eukaryotic genome annotation. OrthoMCL starts with reciprocal best hits within each genome as potential in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as potential ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.
AmoebaDB belongs to the EuPathDB family of databases and is an integrated genomic and functional genomic database for Entamoeba and Acanthamoeba parasites. In its first iteration (released in early 2010), AmoebaDB contains the genomes of three Entamoeba species (see below). AmoebaDB integrates whole genome sequence and annotation and will rapidly expand to include experimental data and environmental isolate sequences provided by community researchers . The database includes supplemental bioinformatics analyses and a web interface for data-mining.
ToxoDB is a genome database for the genus Toxoplasma, a set of single-celled eukaryotic pathogens that cause human and animal diseases, including toxoplasmosis.
This Animal Quantitative Trait Loci (QTL) database (Animal QTLdb) is designed to house all publicly available QTL and trait mapping data (i.e. trait and genome location association data; collectively called "QTL data" on this site) on livestock animal species for easily locating and making comparisons within and between species. New database tools are continuely added to align the QTL and association data to other types of genome information, such as annotated genes, RH / SNP markers, and human genome maps. Besides the QTL data from species listed below, the QTLdb is open to house QTL/association date from other animal species where feasible. Note that the JAS along with other journals, now require that new QTL/association data be entered into a QTL database as part of their publication requirements.