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Biclustering of High-throughput Gene Expression Data with Bicluster Miner
2012 IEEE 12th International Conference on Data Mining Workshops, 2012During recent years, many biclustering algorithms have been developed for the analysis of gene expression data to complement and expand the capabilities of traditional clustering methods. With biclustering, genes with similar expression profiles can be identified not only over the whole data set but also across subsets of experimental conditions ...
András Király +3 more
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A Combinatoric biclustering algorithm
2011The unsupervised analysis of gene expression data plays a very important role in Genetics experiments. That is why a lot of clustering and biclustering techniques have been proposed. Our choice of biclustering methods is motivated by the accuracy in the obtained results and the possibility to find not only rows or columns that provide a partition of ...
Ekaterina Nosova +2 more
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Biclustering of expression data.
Proceedings. International Conference on Intelligent Systems for Molecular Biology, 2001An efficient node-deletion algorithm is introduced to find submatrices in expression data that have low mean squared residue scores and it is shown to perform well in finding co-regulation patterns in yeast and human. This introduces "biclustering", or simultaneous clustering of both genes and conditions, to knowledge discovery from expression data ...
Yizong Cheng, George M. Church
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International Journal of Biomedical Engineering and Technology, 2018
Clustering has various methods for solving the different research problems in biological domain. Analysis of gene expression data in biomedical filed is very critical task, in which various algorithms are proposed under different experimental conditions.
E. Saravana Kumar +3 more
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Clustering has various methods for solving the different research problems in biological domain. Analysis of gene expression data in biomedical filed is very critical task, in which various algorithms are proposed under different experimental conditions.
E. Saravana Kumar +3 more
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Boolean Representation for Exact Biclustering
Fundamenta Informaticae, 2018Biclustering is a branch of data analysis, whereby the goal is to find two–dimensional subgroups in a matrix of scalars. We introduce a new approach for biclustering discrete and binary matrices on the basis of boolean function analysis. We draw the correspondence between non–extendable (maximal with respect to inclusion) exact biclusters and prime ...
Marcin Michalak 0001, Dominik Slezak
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2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006
Uncovering genetic pathways is equivalent to finding clusters of genes with expression levels that evolve coherently under subsets of conditions. This can be done by applying a biclustering procedure to gene expression data. Given a microarray data set with M genes and N conditions, we define a bicluster with coherent evolution as a subset of genes ...
Ahmed H. Tewfik +2 more
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Uncovering genetic pathways is equivalent to finding clusters of genes with expression levels that evolve coherently under subsets of conditions. This can be done by applying a biclustering procedure to gene expression data. Given a microarray data set with M genes and N conditions, we define a bicluster with coherent evolution as a subset of genes ...
Ahmed H. Tewfik +2 more
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Possibilistic biclustering algorithm for discovering value-coherent overlapping δ-biclusters
International Journal of Machine Learning and Cybernetics, 2013One of the important tools for analyzing gene expression data is biclustering method. It focuses on finding a subset of genes and a subset of experimental conditions that together exhibit coherent behavior. However, most of the existing biclustering algorithms find exclusive biclusters, which is inappropriate in the context of biology. Since biological
Chandra Das, Pradipta Maji
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Foundations of Rough Biclustering
2012Amongst the algorithms for biclustering using some rough sets based steps none of them uses the formal concept of rough bicluster with its lower and upper approximation. In this short article the new foundations of rough biclustering are described. The new relation β generates β−description classes that build the rough bicluster defined with its lower ...
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