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Information engineering infrastructure for life sciences and its implementation in China

Information engineering infrastructure for life sciences and its implementation in China
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摘要 Biological data,represented by the data from omics platforms,are accumulating exponentially.As some other data-intensive scientific disciplines such as high-energy physics,climatology,meteorology,geology,geography and environmental sciences,modern life sciences have entered the information-rich era,the era of the 4th paradigm.The creation of Chinese information engineering infrastructure for pan-omics studies(CIEIPOS) has been long overdue as part of national scientific infrastructure,in accelerating the further development of Chinese life sciences,and translating rich data into knowledge and medical applications.By gathering facts of current status of international and Chinese bioinformatics communities in collecting,managing and utilizing biological data,the essay stresses the significance and urgency to create a 'data hub' in CIEIPOS,discusses challenges and possible solutions to integrate,query and visualize these data.Another important component of CIEIPOS,which is not part of traditional biological data centers such as NCBI and EBI,is omics informatics.Mass spectroscopy platform was taken as an example to illustrate the complexity of omics informatics.Its heavy dependency on computational power is highlighted.The demand for such power in omics studies is argued as the fundamental function to meet for CIEIPOS.Implementation outlook of CIEIPOS in hardware and network is discussed. Biological data, represented by the data from omics platforms, are accumulating exponentially. As some other data-intensive scien- tific disciplines such as high-energy physics, climatology, meteorology, geology, geography and environmental sciences, modern life sciences have entered the information-rich era, the era of the 4th paradigm. The creation of Chinese information engineering infra- structure for pan-omics studies (CIEIPOS) has been long overdue as part of national scientific infrastructure, in accelerating the fur- ther development of Chinese life sciences, and translating rich data into knowledge and medical applications. By gathering facts of current status of international and Chinese bioinformatics communities in collecting, managing and utilizing biological data, the essay stresses the significance and urgency to create a 'data hub' in CIEIPOS, discusses challenges and possible solutions to integrate, query and visualize these data. Another important component of CIEIPOS, which is not part of traditional biological data centers such as NCBI and EBI, is omics informatics. Mass spectroscopy platform was taken as an example to illustrate the complexity of omics in- formatics. Its heavy dependency on computational power is highlighted. The demand for such power in omics studies is argued as the fundamental function to meet for CIEIPOS. Implementation outlook of CIEIPOS in hardware and network is discussed.
出处 《Science China(Life Sciences)》 SCIE CAS 2013年第3期220-227,共8页 中国科学(生命科学英文版)
基金 financial support of Taicang government,Suzhou,China
关键词 现代生命科学 信息化工程 基础设施 中国 生物数据 数据中心 数据密集型 生物信息学 biological database services, omics informatics, information engineering infrastructure for pan-omics studies
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  • 1Schadt E E, Linderman M D, Sorenson J, et al. Computational solu tions to large-scale data management and analysis. Nat Rev Genet, 2010, 11:647-657.
  • 2Smith A, Balazinska M, Baru C, et al. Biology and data-intensive scientific discovery in the beginning of the 21st century. OMICS, 2011, 15:209-212.
  • 3Kolker E, Stewart E, Ozdemir V. Opportunities and challenges forthe life sciences community. OMICS, 2012, 16:136-147.
  • 4Crosswell L, Thornton J. ELIXIR: a distributed infrastructure for European biological data. Trends Biotechnol, 2012, 30:241-242.
  • 5Bu D C, Yu K T, Sun S L, et al. NONCODE v3.0: integrative anno- tation of long noncoding RNAs. Nucleic Acids Res, 2012, 40: D210- D215.
  • 6Wei L P, Yu J. Bioinformatics in China: a personal perspective. PLoS Comput Biol, 2008, 4:e1000020.
  • 7Zdobnov E M, Lopez R, Apweiler R, et al. The EBI SRS serv- er-recent developments. Bioinformatics, 2002, 118:368-373.
  • 8Saltz J H, Oster S, Hastings S L, et al. Integrating heterogeneous rules-engine technologies with caGrid. AMIA Annu Symp Proc, 2007, 11:1099.
  • 9Smedley D, Haider S, Ballester B, et al. BioMart-iological queries made easy. BMC Genomics, 2009, 14:22.
  • 10Livne O E, Schultz N D, Narus S P. Federated querying architecture with clinical & translational health IT application. J Med Syst, 2011, 35:1211-1224.

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