Autors: Gancheva, V. S., Borovska, P. B.
Title: SOA based system for big genomic data analytics and knowledge discovery
Keywords: Breast cancer data,Genomic data, Large data, Results visuali

Abstract: The volume of stored genomic data has increased significantly in the recent years. Main challenge in their analysis and knowledge discovery is to suggest advanced and efficient tools, methods and technologies for access and processing. SOA based system for adaptive knowledge discovery and decision making based on big genomic data analytics is proposed in this paper. The system architecture is comprised of web services for data integration, preprocessing of large data streams, knowledge discovery based on genomic data analytics, knowledge interpretation and results visualization. The functionality of the developed system is explained. A web service for breast cancer data processing has been developed for the purpose of system testing and validation. The proposed system architecture allows scientists an easy, fast and flexible approach for data processing.



    Proceedings of the 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2019., vol. IDAACS 2019, issue 10, pp. 536-541, 2019, France, IEEE Inc, DOI 10.1109/IDAACS.2019.8924370

    Copyright IEEE

    Цитирания (Citation/s):
    1. A. Mavrogiorgou et al., "beHEALTHIER: A Microservices Platform for Analyzing and Exploiting Healthcare Data," 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), 2021, pp. 283-288, doi: 10.1109/CBMS52027.2021.00078. - 2021 - в издания, индексирани в Scopus или Web of Science
    2. Niharika Gupta, Baij Nath Kaushik, Prognosis and Prediction of Breast Cancer Using Machine Learning and Ensemble-Based Training Model, The Computer Journal, 2021;, bxab145, - 2021 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus