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Simultaneous Clustering and Feature Weighting Using Multiobjective Optimization for Identifying Functionally Similar miRNAs.

Abstract：

:MicroRNAs (miRNAs) are a type of RNAs, which are responsible for monitoring the gene expression values. Recent research asserts that miRNAs form some clustering on chromosomes. The miRNAs belonging to a particular cluster are highly similar in terms of their activity and they are termed as "coregulated" miRNAs. The current paper presents an approach that simultaneously performs two tasks: i) clustering of miRNAs into different categories based on some similarity measures ii) identification of proper weight values for different time points with respect to which expression values are available. In general, a large number of expression values are available for a given miRNA data set. All these values may not be suitable to be used equally to measure the similarity between two miRNAs. In the current study, the problem of proper selection of weight values for different time points and then determining the proper partitioning from the given miRNA data set utilizing the similarity computed using the new set of weight values is formulated as an optimization problem where several cluster validity indices are optimized as the goodness measures. To that end, a multiobjective differential evolution based optimization technique is utilized. The supremacy of the proposed technique is tested on three miRNA data sets in comparison to some recent approaches in terms of some popular performance measures like Silhouette index and DB-index. The observations are further supported by statistical and biological significance tests. Supplementary information is available at https://www.iitp.ac.in/~sriparna/journals.html.

journal_name

IEEE J Biomed Health Inform

journal_title

IEEE journal of biomedical and health informatics

authors

Saha S,Acharya S,K K,Miriyala S

doi

10.1109/JBHI.2017.2784898

subject

Has Abstract

pub_date

2018-09-01 00:00:00

pages

1684-1690

issue

5

eissn

2168-2194

issn

2168-2208

journal_volume

22

pub_type

杂志文章

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