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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.
We are working on a new version of ALFRED web interface. The current web interface will not be available from December 15th, 2023. There will be a period where a public web interface is not available for viewing ALFRED data. Expected date for the deployment of the new ALFRED web interface with minimum functions is March 1st, 2024 --------------------------------------------- ALFRED is a free, web-accessible, curated compilation of allele frequency data on DNA sequence polymorphisms in anthropologically defined human populations. ALFRED is distinct from such databases as dbSNP, which catalogs sequence variation.
GeneWeaver combines cross-species data and gene entity integration, scalable hierarchical analysis of user data with a community-built and curated data archive of gene sets and gene networks, and tools for data driven comparison of user-defined biological, behavioral and disease concepts. Gene Weaver allows users to integrate gene sets across species, tissue and experimental platform. It differs from conventional gene set over-representation analysis tools in that it allows users to evaluate intersections among all combinations of a collection of gene sets, including, but not limited to annotations to controlled vocabularies. There are numerous applications of this approach. Sets can be stored, shared and compared privately, among user defined groups of investigators, and across all users.