[PDF] Top 20 A robust approach based on Weibull distribution for clustering gene expression data
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A robust approach based on Weibull distribution for clustering gene expression data
... (SOM) clustering algorithms to the same gene sub- sets as the WDCM and obtain the gene clusters, respec- ...the gene clusters produced by WDCM to those produced by the other ...the gene ... See full document
9
Fuzzy Mining Approach for Gene Clustering and Gene Function Prediction
... Microarray Gene data by using data mining and fuzzy ...microarray gene data based on fuzzy association ...rule based approach for solving problems rather than ... See full document
10
ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY
... conditions based on a proposed criterion. The method is illustrated on yeast gene expression ...the approach dynamically adjusts the memberships of genes and ...This approach proves to ... See full document
5
Stable Graphical Models
... of gene expression profiles are a popular tool (Friedman et ...common approach to network models of gene expression involves learning linear regression- based Gaussian graphical ... See full document
36
Parallel K Means Clustering for Gene Expression Data on SNOW
... of data and different number of computing ...for data pre-processed by PCA, leveraging multiple cores (hereafter also referred to as workers or nodes) available in a desktop ...This approach is ... See full document
5
Consensus clustering and functional interpretation of gene expression data
... showing gene- expression clustering algorithm discordance using a direct measurement of similarity: the weighted-kappa ...between clustering meth- ods, we have developed techniques for ... See full document
18
A temporal precedence based clustering method for gene expression microarray data
... the data to the unknown model that describes the ...are based on statistical mixture models which assume that data is generated by a finite mixture of underlying probability distributions, with each ... See full document
26
Improved robustness in time series analysis of gene expression data by polynomial model based clustering
... large data sets that often contain noise and considerable missing ...Typical clustering meth- ods such as hierarchical clustering or partitional algorithms can often be adversely affected by such ... See full document
11
Clustering gene expression data using a diffraction‐inspired framework
... of gene expression levels. The large amount of captured data challenges conventional statistical tools for analysing and finding inherent correlations between genes and ...unsupervised ... See full document
19
Efficient Clustering for Gene Expression Data
... primary approach to gathering biological data. [1] These data can be used to the actual clinical application of gene expression data analysis and guide development of drugs and ... See full document
6
Semi-supervised consensus clustering for gene expression data analysis
... for gene expression datasets is ...for clustering microarray data. A study on semi-supervised clustering shows that with small amounts of prior knowledge, search-based ... See full document
13
Robust Fuzzy Cluster Ensemble on Cancer Gene Expression Data
... cancer gene ex- pression data clustering research, which may cause inaccurate results and mislead the underlying biological ...A clustering method that is robust to noise is highly de- ... See full document
9
GENE EXPRESSION DATA ANALYSIS USING DATA MINING ALGORITHMS FOR COLON CANCER
... of Data mining is used in various medical applications like tumor classification, protein structure prediction, gene classification, cancer classification based on microarray data, ... See full document
7
Robust hypergraph regularized non-negative matrix factorization for sample clustering and feature selection in multi-view gene expression data
... the data are sometimes negative, so semi- non-negative matrix factorization (Semi-NMF) and convex non-negative matrix factorization (Convex-NMF) are derived to solve the problem of positive and negative ... See full document
10
Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution
... Abstract: In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two ... See full document
5
Towards gene network estimation with structure learning
... of gene interactions. A gene usually collaborates with other genes in order to ...analyse gene expression data, other researchers have enhanced the technique ...the gene network ... See full document
5
The Generalized Transmuted Weibull Distribution for Lifetime Data
... transmuted Weibull (GT-W) ...generated distribution. Based on the generalized transmuted-G (GT-G) family of distributions, we construct the new five-parameter GT-W model and give a comprehensive ... See full document
24
A robust fuzzy rule based integrative feature selection strategy for gene expression data in TCGA
... of gene signatures that could distinguish the cancer patients from the ...the robust gene features. Methods: In this work, a gene signature selection strategy for TCGA data was proposed ... See full document
9
Model Selection for Investigation of the Field Distribution in a Reverberation Chamber
... It is shown that by loading the RC it is possible to create Rician distributed Cartesian field. According to [14], the unstirred multipath component (UMC) has the same effect as the line-of-sight (LOS) component. By ... See full document
15
Classification of Cancer Gene Subtypes from Clustering of Gene Expression Data
... the gene subtypes co-clustering algorithm called Network assisted Co-clustering for the Identification of cancer Subtypes ...factorization-based clustering family in this ...as ... See full document
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