However, a new generation of genome-integrity experiments combining computational modeling, data analytics, and high-throughput sequencing are emerging to link mechanisms to patterns.
This is increasingly fueled by new discoveries in computer science and data science, coupled with the quick-paced ubiquity and massive use of computational and data analytics within a variety of urban domains to address the complex challenges of sustainability and urbanization facing the city.
Complemented by computational and data analytics techniques, these methods allow for the comprehensive investigation of genomes, transcriptomes, proteomes, and metabolomes, with an ultimate goal to perform a global profiling of health and disease in unprecedented detail [ 5].
Additionally, Das is working on improving the diagnostic accuracy of ear-infections using computational imaging and data analytics.
The MIEP program integrates computational modeling, big data analytics, portal science, and procedural knowledge to engineer synthetic information processing representations of the immune system.
This chapter describes the cyberinfrastructure required to integrate computational modeling, big data analytics, portal science, and procedural knowledge to engineer synthetic systems-wide information processing representations of immune responses.
The techniques include computational intelligence, big data analytics, social media techniques, multi-objective optimization, regression, classification, clustering, biological data processing, text processing, and image/video analysis.
A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches.
Statistical Science at Duke is the world's leading graduate research and educational environment for Bayesian statistics, emphasizing the major themes of 21st century statistical science: foundational concepts of statistics, theory and methods of complex stochastic modeling, interdisciplinary applications of statistics, computational statistics, big data analytics, and machine learning.
The course is a journey into the foundations of Parallel Computing at the intersection of large-scale computational science and big data analytics.
It blends elements of hardware, software and networks together with digital sensors, smart devices, Internet technologies, big data analytics, computational intelligence and intelligent systems to realize various innovative applications.
