[PDF] Top 20 ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY
Has 10000 "ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY" found on our website. Below are the top 20 most common "ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY".
ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY
... conditions based on a proposed criterion. The method is illustrated on yeast gene expression ...a set of biclusters of maximum size, with stronger coherence, and particularly with a reasonable ... See full document
5
A Survey on Data Mining Of Gene Expression Data for Gene Function Prediction
... the gene expression data for predicting the gene functioning for the possibility of cancerous behavior and utilizing the same in prompt and precise ...detail survey of existing ... See full document
7
Clustering Time Series Gene Expression Data Based on Sum-of-Exponentials Fitting
... tal data, and consists in solving a set of linear equations for the recurrence equation that the signals ...A survey on vari- ous algorithms for fitting a sum of exponentials can be found in [19], ... See full document
15
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
Consensus clustering and functional interpretation of gene expression data
... is set to search for 13 and 40 ...ASC data was determined by the number of repeated genes, whereas 40 clusters for the B- cell data was based on previous exploratory data analysis ...SA ... See full document
18
Efficient Clustering for Gene Expression Data
... attribute clustering method which was able to group genes based on their interdependence in order to mine meaningful patterns from the gene expression ...to gene expression ... See full document
6
A robust approach based on Weibull distribution for clustering gene expression data
... cancer gene expression data sets we used, and then visually demon- strated the clustering results obtained using the WDCM for the three data ...the gene clusters produced by the ... See full document
9
A Survey on Parallel Rough Set Based Knowledge Acquisition Using MapReduce from Big Data
... programming approch . Here, One node is elected to be the master node which is responsible for assigning the work, while the rest of the nodes are worker nodes. The input data is divided into n splits and the ... See full document
5
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
Feature Subset Selection using Rough Sets for High Dimensional Data
... The proposed approach removes irrelevant and redundant features using filter and clustering-based method. A cluster consists of features. Each cluster is treated as a single feature and thus dimensionality ... See full document
5
Rough set approach for categorical data clustering
... the data set is assumed to be sufficient for discovering well-defined ...subspace clustering of the ...hierarchical clustering method termed ROCK (Robust Clustering using Links), which ... See full document
47
Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
... in clustering process of categorical ...symbolic data analysis tool now being developed for cluster analysis (D¨untsch & Gediga, ...In rough categorical clustering, mainly the data ... See full document
54
Clustering of Mixed Data Types with Application to Toxicogenomics
... of gene expression analysis. Rather than assaying the expression of genes one at a time, microarray analysis provides the ability to survey genome-wide expression of genes ... See full document
233
A Survey of Software Packages Used for Rough Set Analysis
... (Rough Set Toolkit for Analysis of Data) is a toolkit for analyzing datasets in tabular form using Rough Set Theory [17] ...implements rough-set based rule ... See full document
9
Clustering Techniques Analysis for Microarray Data
... In gene expression data, it is worth to cluster both genes and ...of clustering that can be applied on microarray data: gene based clustering, sample based ... See full document
6
On the selection of appropriate distances for gene expression data clustering
... for clustering short gene time-series, namely, Jack- knife (JK), Short Time-Series Dissimilarity (STS), Local Shape-based Similarity (LSS), YS1, and ...different clustering methods commonly ... See full document
17
Classification of Cancer Gene Subtypes from Clustering of Gene Expression Data
... algorithm based on information bottleneck similarity known as ibFCC proposed by Liu, Wu [3] using similarity ...biomedical data. There are some review papers also available for co-clustering ... See full document
5
An Approach to Improve Quality of Document Clustering by Word Set Based Documenting Clustering Algorithm
... document data sets which have been widely used in document clustering ...these data sets contained 1,504 documents and the largest contained 7,094 ...Classic data set was combined from ... See full document
7
ARIMA METHOD WITH THE SOFTWARE MINITAB AND EVIEWS TO FORECAST INFLATION IN SEMARANG INDONESIA
... Histogram based centroid approach is good but it is initialized randomly and after histogram ...region based centroid segmentation is ...generalized rough intuitionistic fuzzy c-means algorithm has ... See full document
10
Towards gene network estimation with structure learning
... Gene expression is not an independent ...complex. Gene interactions are studied through gene network. Gene network is a group of coordinately expressed genes controlling a particular ... See full document
5
Related subjects