Open AccessA Novel Customized Big Data Analytics Framework for Drug Discovery
Author(s) -
A. Jainul Fathima,
G. Murugaboopathi
Publication year - 2018
Publication title -
journal of cyber security and mobility
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.198
H-Index - 9
eISSN - 2245-4578
pISSN - 2245-1439
DOI - 10.13052/2245-1439.7111
Subject(s) - big data , data science , computer science , analytics , drug discovery , knowledge extraction , data analysis , business process discovery , field (mathematics) , process (computing) , data mining , work in process , bioinformatics , engineering , business process , mathematics , operations management , business process modeling , pure mathematics , biology , operating system
Drug discovery is related to analytics as the method requires a technique to handle the extremely large volume of structured and unstructured biomedical data of multi-dimensional and complexity from pharmaceutical companies. To tackle the complexity of data and to get better insight into the data, big data analytics can be used to integrate the massive amount of pharmaceutical data and computational tools in an analytic framework. This paper presents an overview of big data analytics in the field of drug discovery and outlines an analytic framework which can be applied to computational drug discovery process and briefly discuss the challenges. Hence, big data analytics may contribute to better drug discovery.