Title :
Block Mixture Model for the Biclustering of Microarray Data
Author :
Saber, H.B. ; Elloumi, Mourad ; Nadif, Mohamed
Author_Institution :
Unit of Res. of Technol. of Inf. & Commun., Univ. of Tunis, Tunis, Tunisia
fDate :
Aug. 29 2011-Sept. 2 2011
Abstract :
An attractive way to make biclustering of genes and conditions is to adopt a Block Mixture Model (BMM). Approaches based on a BMM operate thanks to a Block Expectation Maximization (BEM) algorithm and/or a Block Classification Expectation Maximization (BCEM) one. The drawback of these approaches is their difficulty to choose a good strategy of initialization of the BEM and BCEM algorithms. This paper introduces existing biclustering approaches adopting a BMM and suggests a new fuzzy biclustering one. Our approach enables to choose a good strategy of initialization of the BEM and BCEM algorithms.
Keywords :
expectation-maximisation algorithm; fuzzy set theory; pattern clustering; block classification expectation maximization; block expectation maximization algorithm; block mixture model; fuzzy biclustering; microarray data biclustering; Biological system modeling; Classification algorithms; Clustering algorithms; Educational institutions; Equations; Gene expression; Mathematical model; biclustering; block classification expectation maximization algorithm; block expectation maximization algorithm; block mixture model; fuzzy strategy; microarray data;
Conference_Titel :
Database and Expert Systems Applications (DEXA), 2011 22nd International Workshop on
Conference_Location :
Toulouse
Print_ISBN :
978-1-4577-0982-1
DOI :
10.1109/DEXA.2011.17