A Service Computing Framework for Proteomics Analysis and Collaboration of Pathogenic Mechanism Studies
RIS ID
141872
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.
Publication Details
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.