TY - GEN
T1 - A service computing framework for proteomics analysis and collaboration of pathogenic mechanism studies
AU - Chen, Huaming
AU - Li, Fucun
AU - Sun, Geng
AU - Zhang, Xuyun
AU - Dong, Xianjun
AU - Wang, Lei
AU - Liao, Kewen
AU - Shen, Haifeng
AU - Shen, Jun
PY - 2020
Y1 - 2020
N2 - 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-the- art 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.
AB - 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-the- art 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.
KW - service computing
KW - pathogenic mechanism
KW - proteomics
KW - Service computing
KW - Proteomics
KW - Pathogenic mechanism
UR - http://www.scopus.com/inward/record.url?scp=85099214900&partnerID=8YFLogxK
U2 - 10.1109/SCC49832.2020.00069
DO - 10.1109/SCC49832.2020.00069
M3 - Conference proceeding contribution
T3 - Proceedings of the IEEE International Conference on Services Computing SCC
SP - 463
EP - 465
BT - Proceedings - 2020 IEEE 13th International Conference on Services Computing, SCC 2020
PB - Institute of Electrical and Electronics Engineers (IEEE)
CY - Piscataway, NJ
T2 - 13th IEEE International Conference on Services Computing, SCC 2020
Y2 - 18 October 2020 through 24 October 2020
ER -