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A Service Computing Framework for Proteomics Analysis and Collaboration of Pathogenic Mechanism Studies

Conference Paper


Abstract


  • The booming of proteomics data has positioned

    multiple disciplines and research areas in a more complicated

    and challenging place. Moreover, the proteomics data of any

    defined research interests, such as for pathogenic mechanism

    studies of infectious diseases, have presented unstructured

    and heterogeneous characteristics. Thus, a service computing

    framework for proteomics analysis is desired to bring biologists

    and computer scientists into this area seamlessly and efficiently.

    With this regard, this work is dedicated to detail the proteomics

    analysis and collaboration process of pathogenic mechanism

    studies. We articulate this framework to serve the requirements

    and ease the task design by broadly reviewing the state-of-theart

    research and development efforts and collectively designing

    different informative stages. Thus, the framework has a focus of

    distilling different aspects, including data curation, resources

    distribution, standard construction and computational tasks

    identification, into the proteomics analysis. The framework is

    designed as Proteomics Analysis as a Service to deepen the

    understanding of the interdisciplinary research.

UOW Authors


  •   Chen, Huaming (external author)
  •   Li, Fucun (external author)
  •   Sun, Geng (external author)
  •   Zhang, Xuyun (external author)
  •   Dong, Xianjun (external author)
  •   Wang, Lei
  •   Liao, Kewen (external author)
  •   Shen, Haifeng (external author)
  •   Shen, Jun

Publication Date


  • 2020

Citation


  • Chen, H., Li, F., Sun, G., Zhang, X., Dong, X., Wang, L., Liao, K., Shen, H. & Shen, J. (2020). A Service Computing Framework for Proteomics Analysis and Collaboration of Pathogenic Mechanism Studies. IEEE International Conference on Services Computing (pp. 463-465). United States: IEEE.

Scopus Eid


  • 2-s2.0-85099214900

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/4444

Start Page


  • 463

End Page


  • 465

Place Of Publication


  • United States

Abstract


  • The booming of proteomics data has positioned

    multiple disciplines and research areas in a more complicated

    and challenging place. Moreover, the proteomics data of any

    defined research interests, such as for pathogenic mechanism

    studies of infectious diseases, have presented unstructured

    and heterogeneous characteristics. Thus, a service computing

    framework for proteomics analysis is desired to bring biologists

    and computer scientists into this area seamlessly and efficiently.

    With this regard, this work is dedicated to detail the proteomics

    analysis and collaboration process of pathogenic mechanism

    studies. We articulate this framework to serve the requirements

    and ease the task design by broadly reviewing the state-of-theart

    research and development efforts and collectively designing

    different informative stages. Thus, the framework has a focus of

    distilling different aspects, including data curation, resources

    distribution, standard construction and computational tasks

    identification, into the proteomics analysis. The framework is

    designed as Proteomics Analysis as a Service to deepen the

    understanding of the interdisciplinary research.

UOW Authors


  •   Chen, Huaming (external author)
  •   Li, Fucun (external author)
  •   Sun, Geng (external author)
  •   Zhang, Xuyun (external author)
  •   Dong, Xianjun (external author)
  •   Wang, Lei
  •   Liao, Kewen (external author)
  •   Shen, Haifeng (external author)
  •   Shen, Jun

Publication Date


  • 2020

Citation


  • Chen, H., Li, F., Sun, G., Zhang, X., Dong, X., Wang, L., Liao, K., Shen, H. & Shen, J. (2020). A Service Computing Framework for Proteomics Analysis and Collaboration of Pathogenic Mechanism Studies. IEEE International Conference on Services Computing (pp. 463-465). United States: IEEE.

Scopus Eid


  • 2-s2.0-85099214900

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/4444

Start Page


  • 463

End Page


  • 465

Place Of Publication


  • United States