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Introduction of the Korea BioData Station (K-BDS) for sharing biological data

  • Byungwook Lee (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Seungwoo Hwang (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Pan-Gyu Kim (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Gunwhan Ko (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Kiwon Jang (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Sangok Kim (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Jong-Hwan Kim (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Jongbum Jeon (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Hyerin Kim (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Jaeeun Jung (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Byoung-Ha Yoon (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Iksu Byeon (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Insu Jang (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Wangho Song (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Jinhyuk Choi (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology) ;
  • Seon-Young Kim (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience & Biotechnology)
  • Received : 2022.12.09
  • Accepted : 2023.03.06
  • Published : 2023.03.31

Abstract

A wave of new technologies has created opportunities for the cost-effective generation of high-throughput profiles of biological systems, foreshadowing a "data-driven science" era. The large variety of data available from biological research is also a rich resource that can be used for innovative endeavors. However, we are facing considerable challenges in big data deposition, integration, and translation due to the complexity of biological data and its production at unprecedented exponential rates. To address these problems, in 2020, the Korean government officially announced a national strategy to collect and manage the biological data produced through national R&D fund allocations and provide the collected data to researchers. To this end, the Korea Bioinformation Center (KOBIC) developed a new biological data repository, the Korea BioData Station (K-BDS), for sharing data from individual researchers and research programs to create a data-driven biological study environment. The K-BDS is dedicated to providing free open access to a suite of featured data resources in support of worldwide activities in both academia and industry.

Keywords

Acknowledgement

We thank our users for submitting data, sending suggestions, reporting bugs and becoming involved in community curation. This work was supported by a grant from the National Research Foundation of Korea (NRF-2020M3A9I6A01036057). A portion of the data used for this study was obtained from the K-BDS (IDs: PRJKA121272 and PRJKA230562) at the KOBIC.

References

  1. Sielemann K, Hafner A, Pucker B. The reuse of public datasets in the life sciences: potential risks and rewards. PeerJ 2020;8:e9954.
  2. West JD, Bergstrom CT. Misinformation in and about science. Proc Natl Acad Sci U S A 2021;118:e1912444117.
  3. Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res 2016;44:D67-D72. https://doi.org/10.1093/nar/gkv1276
  4. Burley SK, Berman HM, Kleywegt GJ, Markley JL, Nakamura H, Velankar S. Protein Data Bank (PDB): the single global macromolecular structure archive. Methods Mol Biol 2017;1607:627-641. https://doi.org/10.1007/978-1-4939-7000-1_26
  5. Arita M, Karsch-Mizrachi I, Cochrane G. The international nucleotide sequence database collaboration. Nucleic Acids Res 2021;49:D121-D124. https://doi.org/10.1093/nar/gkaa967
  6. Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC, et al. Database resources of the national center for biotechnology information. Nucleic Acids Res 2022;50:D20-D26. https://doi.org/10.1093/nar/gkab1112
  7. Cantelli G, Cochrane G, Brooksbank C, McDonagh E, Flicek P, McEntyre J, et al. The European Bioinformatics Institute: empowering cooperation in response to a global health crisis. Nucleic Acids Res 2021;49:D29-D37. https://doi.org/10.1093/nar/gkaa1077
  8. Fukuda A, Kodama Y, Mashima J, Fujisawa T, Ogasawara O. DDBJ update: streamlining submission and access of human data. Nucleic Acids Res 2021;49:D71-D75. https://doi.org/10.1093/nar/gkaa982
  9. CNDB-NGDC Members and Partners. Database resources of the National Genomics Data Center, China National Center for Bioinformation in 2021. Nucleic Acids Res 2021;49:D18-D28. https://doi.org/10.1093/nar/gkaa1022
  10. Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, et al. Minimum information about a microarray experiment (MIAME): toward standards for microarray data. Nat Genet 2001;29:365-371. https://doi.org/10.1038/ng1201-365
  11. Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: archive for functional genomics data sets: update. Nucleic Acids Res 2013;41:D991-D995. https://doi.org/10.1093/nar/gks1193
  12. Sarkans U, Gostev M, Athar A, Behrangi E, Melnichuk O, Ali A, et al. The BioStudies database-one stop shop for all data supporting a life sciences study. Nucleic Acids Res 2018;46:D1266- D1270. https://doi.org/10.1093/nar/gkx965
  13. Singh J. FigShare. J Pharmacol Pharmacother 2011;2:138-139. https://doi.org/10.4103/0976-500X.81919
  14. Ko G, Kim PG, Yoon J, Han G, Park SJ, Song W, et al. Closha: bioinformatics workflow system for the analysis of massive sequencing data. BMC Bioinformatics 2018;19:43.