Combining a Ensemble Clustering Method and a New Similarity Criterion for Modeling the Hereditary Behavior of Diseases

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Mojarad Musa; PARVIN HAMID; Nejatiyan Samad; Bagheri Fard Karam Allah

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Paper Information

Journal: SIGNAL AND DATA PROCESSING Year:2021 | Volume:18 | Issue:2 (48) Page(s): 97-114

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Title

Combining a Ensemble Clustering Method and a New Similarity Criterion for Modeling the Hereditary Behavior of Diseases

Author(s)

Mojarad Musa | PARVIN HAMID | Nejatiyan Samad | Bagheri Fard Karam Allah | Issue Writer Certificate

Keywords

Intercellular communication

Improved clustering

Graph topological structure

Phantom 5 data set

Abstract

There are many theories about the causes of hereditary diseases, but physician believe that both the genetic and environmental factors simultaneously play an important role in the development and progression of these diseases, although the extent to which this effect is not yet clear. In order to detect effective genes in the development of diseases, it is necessary to achieve the relationship between cells/tissues. The interaction between different cells/tissues can be demonstrated by expressing the gene between them. By sampling chromosomes, useful information is obtained about the type of disease and how it is transmitted. By examining this information, you can identify disorders that have led to highly altered changes. In this paper, the recognition of intercellular and inter-tissue interactions in various diseases has been done according to the characteristics of the topological structure of the graph and an improved cumulative clustering method. The proposed method has two stages; in the first step, several clustering models are combined to identify the initial relationships between cells or tissues in order to produce better results than individual algorithms. In the second stage, the similarity between cells or tissues in each cluster is calculated using a similarity criterion based on the topological structure of the graph. Eventually, the maximum similarity between cells or tissues in each cluster is used to discover the relationship between diseases. To evaluate the performance of the proposed method, several UCI datasets and the Phantom 5 dataset have been used. The results of the proposed method on the phantom data set 5 report a silhouette of 0. 901 in 18 clusters for cells and 0. 762 in 13 clusters for tissues.

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APA: Copy

Mojarad, Musa, PARVIN, HAMID, Nejatiyan, Samad, & Bagheri Fard, Karam Allah. (2021). Combining a Ensemble Clustering Method and a New Similarity Criterion for Modeling the Hereditary Behavior of Diseases. SIGNAL AND DATA PROCESSING, 18(2 (48) ), 97-114. SID. https://sid.ir/paper/960711/en

Vancouver: Copy

Mojarad Musa, PARVIN HAMID, Nejatiyan Samad, Bagheri Fard Karam Allah. Combining a Ensemble Clustering Method and a New Similarity Criterion for Modeling the Hereditary Behavior of Diseases. SIGNAL AND DATA PROCESSING[Internet]. 2021;18(2 (48) ):97-114. Available from: https://sid.ir/paper/960711/en

IEEE: Copy

Musa Mojarad, HAMID PARVIN, Samad Nejatiyan, and Karam Allah Bagheri Fard, “Combining a Ensemble Clustering Method and a New Similarity Criterion for Modeling the Hereditary Behavior of Diseases,” SIGNAL AND DATA PROCESSING, vol. 18, no. 2 (48) , pp. 97–114, 2021, [Online]. Available: https://sid.ir/paper/960711/en

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