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Found 8 result(s)
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NONCODE is an integrated knowledge database dedicated to non-coding RNAs (excluding tRNAs and rRNAs). Now, there are 16 species in NONCODE(human, mouse, cow, rat, chicken, fruitfly, zebrafish, celegans, yeast, Arabidopsis, chimpanzee, gorilla, orangutan, rhesus macaque, opossum and platypus).The source of NONCODE includes literature and other public databases. We searched PubMed using key words ‘ncrna’, ‘noncoding’, ‘non-coding’,‘no code’, ‘non-code’, ‘lncrna’ or ‘lincrna. We retrieved the new identified lncRNAs and their annotation from the Supplementary Material or web site of these articles. Together with the newest data from Ensembl , RefSeq, lncRNAdb and GENCODE were processed through a standard pipeline for each species.
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.
CERN, DESY, Fermilab and SLAC have built the next-generation High Energy Physics (HEP) information system, INSPIRE. It combines the successful SPIRES database content, curated at DESY, Fermilab and SLAC, with the Invenio digital library technology developed at CERN. INSPIRE is run by a collaboration of CERN, DESY, Fermilab, IHEP, IN2P3 and SLAC, and interacts closely with HEP publishers, arXiv.org, NASA-ADS, PDG, HEPDATA and other information resources. INSPIRE represents a natural evolution of scholarly communication, built on successful community-based information systems, and provides a vision for information management in other fields of science.
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National ecosystem data bank (EcoDB) is a public professional scientific data repository supported by the National Ecosystem Science Data Center (NESDC) for researchers in ecology and related fields, which provides long-term preservation, publication, sharing and access services of scientific data. EcoDB provides services for both individual researchers and scientific journals. Individuals can use this repository to store, manage and publish scientific data, get feedback from others on the data, and discover scientific data shared by others through this repository. Journals can use the repository to gather, manage and review the supporting data of submitted paper. At the same time, journals can timely publish these supporting data according to their own data policies.
GigaDB primarily serves as a repository to host data and tools associated with articles published by GigaScience Press; GigaScience and GigaByte (both are online, open-access journals). GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support a unit-of-work (article or study). GigaDB allows the integration of manuscript publication with supporting data and tools.
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<<<!!!<<< 2019-12-23: the repository is offline >>>!!!>>> Introduction of genome-scale metabolic network: The completion of genome sequencing and subsequent functional annotation for a great number of species enables the reconstruction of genome-scale metabolic networks. These networks, together with in silico network analysis methods such as the constraint based methods (CBM) and graph theory methods, can provide us systems level understanding of cellular metabolism. Further more, they can be applied to many predictions of real biological application such as: gene essentiality analysis, drug target discovery and metabolic engineering
The WDC is concerned with the collection, management, distribution and utilization of data from Chinese provinces, autonomous regions and counties,including: Resource data:management,distribution and utlilzation of land, water, climate, forest, grassland, minerals, energy, etc. Environmental data:pollution,environmental quality, change, natural disasters,soli erosion, etc. Biological resources:animals, plants,wildlife Social economy:agriculture, industry, transport, commerce,infrastructure,etc. Population and labor Geographic background data on scales of 1:4M,1:1M, 1:(1/2)M, 1:2500, etc.
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The mission of ChiCTR is to “unite clinicians, clinical epidemiologists, biostatisticians, epidemiologists and healthcare managers both at home and abroad, to manage clinical trials in a strict and scientific manner, and to promote their quality in China, so as to provide reliable evidence from clinical trials for health care workers, consumers and medical policy decision makers, and also to use medical resources more effectively to provide better service for Chinese people and all human beings.