[PDF] Top 20 Clustering of Leukemia Patients via Gene Expression Data Analysis
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Clustering of Leukemia Patients via Gene Expression Data Analysis
... various gene expression datasets with abundant information that can be very helpful for many meaningful biomedical applications such as prediction, prevention, diagnosis and treatment of diseases, ... See full document
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Semi-supervised consensus clustering for gene expression data analysis
... Simple clustering methods such as agglomerative hierarchical clustering and k-means have been widely used on gene expression data ...individual clustering algorithms have their ... See full document
13
The Local Maximum Clustering Method and Its Application in Microarray Gene Expression Data Analysis
... unsupervised data clustering method, called the local maximum clustering (LMC) method, is proposed for identifying clusters in experiment data sets based on research ...and data sets ... See full document
11
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, clustering ... See full document
7
Efficient Clustering for Gene Expression Data
... biological data. [1] These data can be used to the actual clinical application of gene expression data analysis and guide development of drugs and other ...the data mining ... See full document
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Validation of hierarchical gene clusters using repeated measurements
... Hierarchical clustering is an unsupervised technique, which is a common approach to study protein and gene expression ...In clustering, the patterns of expression of different genes are ... See full document
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Consensus clustering and functional interpretation of gene expression data
... The gene-expression profiles from this consensus cluster were visualized by average linkage HC using the programmes Cluster and Treeview [5] (Figure 5) and clustered gene func- tions were ... See full document
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Biclustering of Gene Expression Data using a Two Phase Method
... of gene expression profiling techniques such as DNA microarray has made it possible to simultaneously analyze expression levels for thousands of genes under a number of different conditions ...[1]. ... See full document
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Analysis of Expression Of SIRT1 Gene In Patients With Chronic Myeloid Leukemia Resistant To Imatinib Mesylate
... This study was conducted in the Research Center of Blood and Stem Cell Transplantation of Dr. Shariati Hospital in Tehran, Iran, to investigate the relationship between the expression of SIRT1 gene and drug ... See full document
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On the selection of appropriate distances for gene expression data clustering
... particular clustering methods we considered during our ...both clustering methods and distance measures ...three clustering methods and cancer data, results sug- gest that Rank-Magnitude, ... See full document
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Histone modification signature at myeloperoxidase and proteinase 3 in patients with anti-neutrophil cytoplasmic autoantibody-associated vasculitis
... the expression analysis were un- ...in gene expression in AAV patients for genes encoding Poly- comb Repressor Complex-2 (PRC2) ...PRTN3 via RUNX3, or his- tone demethylase ... See full document
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Analysis of HLA-G Gene Expression in B-Lymphocytes from Chronic Lymphocytic Leukemia Patients
... HLA-G gene expression and an approach with a large number of healthy controls using pure CD19 B- cells is warranted to clarify the ...antigen expression at protein level apart from problems related ... See full document
5
Classification of Cancer Gene Subtypes from Clustering of Gene Expression Data
... biomedical data. There are some review papers also available for co-clustering algorithms which can be referred for more understanding of current trends in these algorithms ...for gene ... See full document
5
Expression of ROR1 Gene in Patients with Acute Lymphoblastic Leukemia
... Increased expression of ROR1 was observed in 55% of ALL ...these data, an arbitrary cut off level of 1 was defined with 100% ...ROR1 expression among subgroups of FAB-ALL was also ...ROR1 ... See full document
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Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia
... prioritized gene expression signatures, lack of concordance is a common observation in clinical trial [64, ...AML gene expression signatures pro- vided the relationship with patient prognosis ... See full document
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Clustering gene expression data using a diffraction‐inspired framework
... component analysis (PCA), as well as singular value decomposition (SVD), are both commonly used linear methods for reducing the dimensionality of the feature ...between data points as it is based on ... See full document
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Parallel K Means Clustering for Gene Expression Data on SNOW
... of data brings in new challenges for data analysis. Gene expression dataset is one such type of data necessitating analytical methods to mine patterns implicit in ...Although ... See full document
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ROUGH SET BASED CLUSTERING OF GENE EXPRESSION DATA: A SURVEY
... in data mining process for exploring natural structure and identifying interesting patterns in underlying data, have proved to be useful in finding co- expressed ...cluster analysis, one wishes to ... See full document
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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
Gene expression signatures for autoimmune disease in peripheral blood mononuclear cells
... diabetes patients were not receiving the same drugs as those in the SLE and RA ...MS patients were being treated with IFN without glucocorticoids; none of the IDDM patients were on ...since ... See full document
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