[PDF] Top 20 Biclustering of Gene Expression Data using a Two Phase Method
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Biclustering of Gene Expression Data using a Two Phase Method
... in two phases. In Phase I a modified version of k means algorithm is used where k clusters are generated and the Hscore of each cluster is ...second phase of the algorithm is implemented where the ... See full document
5
Novel approaches to biclustering and gene functional classification in microarray gene expression data
... ore, gene ex pression datasets may contain as yet undiscovered classes of genes (functional modules) or samples (cell ...model gene functional modules, which may share gene ...large gene ... See full document
143
An Extensive Survey On Biclustering Approaches And Algorithms For Gene Expression Data
... in expression level during several experimental conditions. Gene clusters are not properly recognized when the clustering methods use huge gene expression ...considers gene ... See full document
9
Application of simulated annealing to the biclustering of gene expression data
... Gene expression datasets are continually growing in size as more experiments are carried out, and as experimental capac- ity ...the expression of genes to be highly similar under one set of ... See full document
7
BiFree: An Efficient Biclustering Technique for Gene Expression Data Using Two Layer Free Weighted Bipartite Graph Crossing Minimization
... for gene expression data provides a global view of the ...of gene expression data with simultaneous grouping of genes and ...Several biclustering techniques have been ... See full document
8
Configurable pattern-based evolutionary biclustering of gene expression data
... existing biclustering approaches base their search for biclusters on evaluation ...of biclustering tools that follow different strate- gies and algorithmic concepts which guide the search towards meaningful ... See full document
22
A Weighted Mutual Information Biclustering Algorithm for Gene Expression Data
... dimensional data, whose a subset of genes are co-regulated under a subset of ...of gene expression ...novel biclustering algorithm, which called Weighted Mutual Information Biclustering ... See full document
18
A Hybrid Nelder-Mead Method For Biclustering Of Gene Expression Data
... Therefore, biclustering algorithms have been preferred to standard clustering techniques to identify local patterns from gene expression data ...sets. Biclustering is a data ... See full document
6
A novel biclustering approach with iterative optimization to analyze gene expression data
... of biclustering algorithms has allowed biologists to start unraveling the underlying functional mechanisms in living ...alternative biclustering technique, since it was designed to address the conventional ... See full document
37
BiGGEsTS: integrated environment for biclustering analysis of time series gene expression data
... the expression value it contains (Figure ...for expression matrices with discrete ...3(c)). Expression tables share additional ...each gene by clicking on its row, and be exported as PNG or ... See full document
11
Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data
... disease gene sets compared to the single disease-specific gene ...assigned gene sets by dividing the number of identified gene sets in each functional category by the total number of ... See full document
8
A comparison and evaluation of five biclustering algorithms by quantifying goodness of biclusters for gene expression data
... In our study, the results are generally consistent with several other surveys of biclus- tering algorithms. Like Prelic et al. [5] and Richards et al. [32], we find that ISA is an effective algorithm that can generate ... See full document
10
Biclustering of Gene Expression Data by Correlation-Based Scatter Search
... of data generated by microarray technology is very useful to understand how the genetic information becomes functional gene ...products. Biclustering algorithms can determine a group of genes which ... See full document
17
A Parallel Algorithm for Gene Expressing Data Biclustering
... by using different groups of ...the two dimensions simultaneously. We not only do clustering on gene sequences, but also consider the variety in experimental ...Therefore, biclustering of ... See full document
7
Biclustering for Microarray Data: A Short and Comprehensive Tutorial
... on biclustering for the analysis of gene expression data obtained from microarray ...to gene expression data are limited by the existence of a number of experimental ... See full document
5
Implementation of BiClusO and its comparison with other biclustering algorithms
... of gene expression data is expected to accumulate similar function genes in individual ...the gene side of each bicluster, we calculated hypergeometric p-values corresponding to three ... See full document
15
Greedy Two Way K-Means Clustering For Optimal Coherent Triclsuter
... the gene expression data it not only gives converge quickly but it provides the global solution (Feng Liu, ...the biclustering problem and it provides high accuracy (Baiyi Xie, ...generated ... See full document
6
Pairwise gene GO-based measures for biclustering of high-dimensional expression data
... other two yeast datasets have been downloaded from the supplementary information provided in ...raw data of the human datasets were generated in the context of clinical experiments with patients that suffer ... See full document
19
A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series
... series gene expression data, obtained from microar- ray experiments performed in successive instants of time, can be used to study a wide range of biological problems [1], and to unravel the ... See full document
39
A statistical method for predicting splice variants between two groups of samples using GeneChip® expression array data
... searched two genome browsers for supportive evidence for our ...same gene, which is a pre-requisite for alterna- A Multiple probes are used to quantify the expression value for a gene in ... See full document
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