Liew, Alan Wee-Chung, and Golchin, Maryam (2018) Bicluster Detection by Hyperplane Projection and Evolutionary Optimization. In: Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies. pp. 61-68. From: Bioinformatics 2018: 9th International Joint Conference on Biomedical Engineering Systems and Technologies, 19-21 January 2018, Funchal, Portugal.

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Abstract

Biclustering is a powerful unsupervised learning technique that has different applications in many fields especially in gene expression analysis. This technique tries to group rows and columns in a dataset simultaneously, which is an NP-hard problem. In this paper, a multi-objective evolutionary algorithm is proposed with a heuristic search to solve the biclustering problem. To do so, rows are projected into the column space. Projection decreases the computational cost of geometric biclustering. The heuristic search is done by sample Pearson correlation coefficient over the rows and columns of a dataset to prune unwanted rows and columns. The experimental results on both synthetic and real datasets show the effectiveness of our proposed method.

Item ID:	76979
Item Type:	Conference Item (Research - E1)
ISBN:	978-989-758-280-6
Copyright Information:	© 2018 ScitePress.
Date Deposited:	12 Dec 2022 00:36
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4613 Theory of computation > 461305 Data structures and algorithms @ 100%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 100%
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