DATA REDUCTION TECHNIQUES FOR HIGH DIMENSIONAL BIOLOGICAL DATA

Shyam Mohan J S, P.Shanmugapriya, N.Kumaran

Abstract: High dimensional biological datasets in recent years has been growing rapidly. Extracting the knowledge and analyzing highdimensional biological data is one the key challenges in which variety and veracity are the two distinct characteristics. The question that arises now is, how to perform dimensionality reduction for this heterogeneous data and how to develop a high performance platform to efficiently analyze high dimensional biological data and how to find the useful things from this data. To deeply discuss this issue, this paper begins with a brief introduction to data analytics available for biological data, followed by the discussions of big data analytics and then a survey on various data reduction methods for biological data. We propose a dense clustering algorithm for standard high dimensional biological data

Keywords: Big Data Analytics, Dimensionality Reduction

DOI: https://doi.org/10.15623/ijret.2016.0502058