Integration and Querying of Heterogeneous Omics Semantic Annotations for Biomedical and Biomolecular Knowledge Discovery

Abstract

Background: Exploring various functional aspects of a biological cell system has been a focused research trend for last many decades. Biologists, scientists and researchers are continuously striving for unveiling the mysteries of these functional aspects to improve the health standards of life. For getting such understanding, astronomically growing, heterogeneous and geographically dispersed omics data needs to be critically analyzed. Currently, omics data is available in different types and formats through various data access interfaces. Applications which require offline and integrated data encounter a lot of data heterogeneity and global dispersion issues. Objective: For facilitating especially such applications, heterogeneous data must be collected, integrated and warehoused in such a loosely coupled way so that each molecular entity can computationally be understood independently or in association with other entities within or across the various cellular aspects. Methods: In this paper, we propose an omics data integration schema and its corresponding data warehouse system for integrating, warehousing and presenting heterogeneous and geographically dispersed omics entities according to the cellular functional aspects. Results & Conclusion: Such aspect-oriented data integration, warehousing and data access interfacing through graphical search, web services and application programing interfaces make our proposed integrated data schema and warehouse system better and useful than other contemporary ones.

Performance optimization of IoT based biological systems using deep learning

“…In these systems, performance can be discussed in different application areas at multiple levels of design complexity. For data caching, there are around seven application areas in various distributed biological systems [11][12][13][14][15][16][17][18][19][20][21][22][23] in which caching plays a significant role in the optimization of performance. These areas are a central processing unit, shared memory multiprocessor, distributed shared memory, distributed file management, distributed proxy cache, world wide web, and internet application and integration [24].…”