A Hybrid Model of Gene Expression Profiles Reducing Based on the Complex Use of Fuzzy Inference System and Clustering Quality Criteria

DOI

10.2991/eusflat-19.2019.20How to use a DOI?

Keywords

Gene expression profiles Reducing Fuzzy inference system Clustering quality criteria Shannon entropy Statistical criteria

Abstract

The paper presents the hybrid model of gene expression profiles reducing based on complex use of fuzzy inference system and clustering quality criteria. The average of absolute values, the variance and Shannon entropy of the gene expression profiles were used as the input parameters of fuzzy inference system. The quality of gene expression profiles was used as output parameter of the model. The boundary value of the output parameter of the model was determined based on the minimum value of the clustering quality criteria which takes into account both the character of the objects distribution within clusters relative to the mass centers of the clusters, where these objects are, and the character of the clusters mass centers distribution in the feature space. Practical implementation of the proposed model allows us to divide the gene expression profiles into informative and non-informative objectively for purpose of the further investigation of the character of genes interconnection in the studied object.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sergii Babichev
AU  - Jiří Barilla
AU  - Jiří Fišer
AU  - Jiří Škvor
PY  - 2019/08
DA  - 2019/08
TI  - A Hybrid Model of Gene Expression Profiles Reducing Based on the Complex Use of Fuzzy Inference System and Clustering Quality Criteria
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 128
EP  - 133
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.20
DO  - 10.2991/eusflat-19.2019.20
ID  - Babichev2019/08
ER  -