Jun 8, 2022 · The present paper proposes a new method for differential gene expression identification based on clustering analysis. The difficulty of the ...
Feb 4, 2023 · By taking the advantage of the unsupervised data analysis, an iterative clustering procedure that finds differentially expressed genes shows promising results.
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The present paper aims to extend and by that to improve the iterative clustering procedure for differential gene expression detection. The analytical review ...
This work is mainly focus on constructing the phylogentic tree for Lung cancer genes of Mouse based on experimental values. Here to construct the phylogenetic ...
Oct 20, 2021 · In this study, we report that a model-based clustering algorithm implemented in an R package, MBCluster.Seq, can also be used for DE analysis.
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Feb 4, 2023 · In the present paper, a comparative study of the clustering methods applied for gene expression analysis is presented to explicate the choice of ...
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ICGS is a multi-step algorithm in AltAnalyze which applies intra-gene correlation and hybrid clustering to uniquely resolve novel transcriptionally coherent ...
May 11, 2020 · We present DESC, an unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function.
In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis.
A comparative study of the clustering methods applied for gene expression analysis is presented to explicate the choice ofThe clustering algorithm ...