• Country
    Clear
  • Type
  • Compatibility Level
  • Thematic
  • Jurisdiction
3,387 Data sources

  • NL
  • CN
  • IT
  • AT

  • more_vert
  • more_vert
  • DANS Data Station Life Sciences

    more_vert
  • more_vert
  • The Database of Protein Disorder (DisProt) is a curated database that provides information about intrinsically disordered proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Disordered regions are manually curated from literature. DisProt annotations cover both structural and functional aspects of disorder detected by specific experimental methods.

    more_vert
  • This site provides access to datasets on Cancer research.

    more_vert
  • more_vert
  • more_vert
  • 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.

    more_vert
  • mirDNMR is a database for the collection of gene-centered background DNMRs obtained from different methods and population variation data. The database has the following functions: (i) browse and search the background DNMRs of each gene predicted by four different methods, including GC content (DNMR-GC), sequence context (DNMR-SC), multiple factors (DNMR-MF) and local DNA methylation level (DNMR-DM); (ii) search variant frequencies in publicly available databases, including ExAC, ESP6500, UK10K, 1000G and dbSNP and (iii) investigate the DNM burden to prioritize candidate genes based on the four background DNMRs using three statistical methods (TADA, Binomial and Poisson test). In conclusion, mirDNMR can be widely used to identify the genetic basis of sporadic genetic diseases.

    more_vert
  • chevron_left
  • 3
  • 4
  • 5
  • 6
  • 7
  • chevron_right
3,387 Data sources
  • more_vert
  • more_vert
  • DANS Data Station Life Sciences

    more_vert
  • more_vert
  • The Database of Protein Disorder (DisProt) is a curated database that provides information about intrinsically disordered proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Disordered regions are manually curated from literature. DisProt annotations cover both structural and functional aspects of disorder detected by specific experimental methods.

    more_vert
  • This site provides access to datasets on Cancer research.

    more_vert
  • more_vert
  • more_vert
  • 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.

    more_vert
  • mirDNMR is a database for the collection of gene-centered background DNMRs obtained from different methods and population variation data. The database has the following functions: (i) browse and search the background DNMRs of each gene predicted by four different methods, including GC content (DNMR-GC), sequence context (DNMR-SC), multiple factors (DNMR-MF) and local DNA methylation level (DNMR-DM); (ii) search variant frequencies in publicly available databases, including ExAC, ESP6500, UK10K, 1000G and dbSNP and (iii) investigate the DNM burden to prioritize candidate genes based on the four background DNMRs using three statistical methods (TADA, Binomial and Poisson test). In conclusion, mirDNMR can be widely used to identify the genetic basis of sporadic genetic diseases.

    more_vert
  • chevron_left
  • 3
  • 4
  • 5
  • 6
  • 7
  • chevron_right