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We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant…

Biological Physics · Physics 2009-11-06 G. Getz , E. Levine , E. Domany

In Tri-clustering, a sub-matrix is being created, which exhibit highly similar behavior with respect to genes, conditions and time-points. In this technique, genes with same expression values are discovered across some fragment of time…

Neural and Evolutionary Computing · Computer Science 2018-05-15 Shreya Mishra , Swati Vipsita

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. Identification of co-expressed genes and coherent patterns is the central goal in microarray or…

Computational Engineering, Finance, and Science · Computer Science 2013-07-15 T. Chandrasekhar , K. Thangavel , E. Elayaraja , E. N. Sathishkumar

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. Identification of co-expressed genes and coherent patterns is the central goal in microarray or…

Computational Engineering, Finance, and Science · Computer Science 2012-01-25 T. Chandrasekhar , K. Thangavel , E. Elayaraja

Traditional clustering methods are limited when dealing with huge and heterogeneous groups of gene expression data, which motivates the development of bi-clustering methods. Bi-clustering methods are used to mine bi-clusters whose subsets…

Computer Vision and Pattern Recognition · Computer Science 2020-05-13 Kaijie Xu , Witold Pedrycz , Zhiwu Li , Yinghui Quan , Weike Nie

Biclustering is an unsupervised data mining technique that aims to unveil patterns (biclusters) from gene expression data matrices. In the framework of this thesis, we propose new biclustering algorithms for microarray data. The latter is…

Machine Learning · Computer Science 2018-11-26 Amina Houari

Computational analysis methods including machine learning have a significant impact in the fields of genomics and medicine. High-throughput gene expression analysis methods such as microarray technology and RNA sequencing produce enormous…

Genomics · Quantitative Biology 2022-09-28 Nikita Bhandari , Rahee Walambe , Ketan Kotecha , Satyajeet Khare

Microarray is a technology to quantitatively monitor the expression of large number of genes in parallel. It has become one of the main tools for global gene expression analysis in molecular biology research in recent years. The large…

Quantitative Methods · Quantitative Biology 2015-06-18 Min Xu

Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more…

Artificial Intelligence · Computer Science 2020-05-05 Khalid Raza

Microarray technology is a process that allows thousands of genes simultaneously monitor to various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins,…

Computational Engineering, Finance, and Science · Computer Science 2013-07-16 T. Chandrasekhar , K. Thangavel , E. Elayaraja

The high-throughput data generated by microarray experiments provides complete set of genes being expressed in a given cell or in an organism under particular conditions. The analysis of these enormous data has opened a new dimension for…

Computational Engineering, Finance, and Science · Computer Science 2012-11-12 Khalid Raza , Akhilesh Mishra

Microarray techniques are widely used in Gene expression analysis. These techniques are based on discovering submatrices of genes that share similar expression patterns across a set of experimental conditions with coherence constraint.…

Quantitative Methods · Quantitative Biology 2020-01-27 Bilal Taher , Muhammad. H Fares , Saeed Jalili

To understand complex biological systems, the research community has produced huge corpus of gene expression data. A large number of clustering approaches have been proposed for the analysis of gene expression data. However, extracting…

Computational Engineering, Finance, and Science · Computer Science 2010-03-28 Swathi. H

The expression levels of many thousands of genes can be measured simultaneously by DNA microarrays (chips). This novel experimental tool has revolutionized research in molecular biology and generated considerable excitement. A typical…

Biological Physics · Physics 2007-05-23 Eytan Domany

Motivation: Clustering techniques are routinely applied to identify patterns of co-expression in gene expression data. Co-regulation, and involvement of genes in similar cellular function, is subsequently inferred from the clusters which…

Quantitative Methods · Quantitative Biology 2016-06-10 Patrick E. McSharry , Edmund J. Crampin

Motivation: Modelling methods that find structure in data are necessary with the current large volumes of genomic data, and there have been various efforts to find subsets of genes exhibiting consistent patterns over subsets of treatments.…

Machine Learning · Computer Science 2016-09-15 Kerstin Bunte , Eemeli Leppäaho , Inka Saarinen , Samuel Kaski

In recent years, with the development of microarray technique, discovery of useful knowledge from microarray data has become very important. Biclustering is a very useful data mining technique for discovering genes which have similar…

Computational Engineering, Finance, and Science · Computer Science 2009-09-09 Mohsen lashkargir , S. Amirhassan Monadjemi , Ahmad Baraani Dastjerdi

DNA microarrays are a relatively new technology that can simultaneously measure the expression level of thousands of genes. They have become an important tool for a wide variety of biological experiments. One of the most common goals of DNA…

Methodology · Statistics 2013-07-02 Eric Bair

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively…

Machine Learning · Computer Science 2012-03-15 T. Chandrasekhar , K. Thangavel , E. Elayaraja

Gene expression analysis aims at identifying the genes able to accurately predict biological parameters like, for example, disease subtyping or progression. While accurate prediction can be achieved by means of many different techniques,…

Methodology · Statistics 2008-09-11 Christine De Mol , Sofia Mosci , Magali Traskine , Alessandro Verri
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