Suchergebnisse - microarray data analysis ‐ integrated differential fuzzy clustering for microarray data analysis

Integrated Differential Fuzzy Clustering for Analysis of Microarray Data von Saha, Indrajit, Maulik, Ujjwal

“… This chapter contains sections titled: Introduction Clustering Algorithms and Validity Measure Differential Evolution Based Fuzzy Clustering Experimental …”
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Improvement of new automatic differential fuzzy clustering using SVM classifier for microarray analysis von Saha, Indrajit, Maulik, Ujjwal, Bandyopadhyay, Sanghamitra, Plewczynski, Dariusz

“… In recent year, the problem of clustering in microarray data has been gaining significant attention …”
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Fuzzy clustering analysis of microarray data von Han, Lixin, Zeng, Xiaoqin, Yan, Hong

“… This paper proposes a fuzzy clustering method for microarray data analysis. An advantage of the method is that it used a combination of the fuzzy c-means …”
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Use of multiobjective differential fuzzy clustering with ANN classifier for unsupervised pattern classification: Application to microarray analysis von Saha, Indrajit

“… Fuzzy clustering is an important tool for analyzing microarray gene expression data. However, this fact motivated us to present a new multiobjective evolutionary algorithm using differential evolution and artificial neural network (ANN …”
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Fuzzy mixed-prototype clustering algorithm for microarray data analysis von Liu, Jin, Pham, Tuan D., Yan, Hong, Liang, Zhizhen

“… ) clustering for microarray data analysis. By integrating spherical and hyper-planar cluster prototypes, the FMP is capable of capturing latent data models with both spherical and non-spherical geometric structures …”
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Analysis of microarray data using multiobjective variable string length genetic fuzzy clustering von Mukhopadhyay, A., Bandyopadhyay, S., Maulik, U.

“… In this article, a novel multiobjective variable string length real coded genetic fuzzy clustering scheme for clustering microarray gene expression data has been proposed …”
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Fuzzy ensemble clustering based on random projections for DNA microarray data analysis von Avogadri, Roberto, Valentini, Giorgio

“… Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact that the boundaries …”
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A modified fuzzy co-clustering (MFCC) approach for microarray data analysis von Sheng-Yao Huang, Hsing-Jen Sun, Chuen-Der Huang, I-Fang Chung, Chun-Hung Su

“… Hence, identification of a subset of genes showing similar regulations under subsets of condition in microarray data has become an important research issue …”
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FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data von Fu, Limin, Medico, Enzo

“… Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarray …”
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A two-stage meta-heuristic approach to general type-ii fuzzy clustering for microarray data analysis von Torshizi, Abolfazl Doostparast, Fazel Zarandi, Mohammad Hossein, Niakan Kalhori, Masoomeh Rostam

“… This paper considers the microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of a-planes in general type-2 fuzzy sets …”
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A Hybrid Fuzzy C-Means Clustering for Microarray Gene Expression Data with a Mixture of Principal Component Analysis von Valarmathie, P

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Application of Fuzzy c-Means and Self-organizing maps for genes clustering in mouse brain microarray data analysis von Sheng-Hsiung Chiu, Meng-Hsiun Tsai, Hsieh-Chung Wu, Wei-Chun Chen, Shrestha, U., Sherwin Kuo

“… from them. However, the brain science research still does not have a standard platform to analyze microarray data …”
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Multi-Objective Differential Evolution for Automatic Clustering with Application to Micro-Array Data Analysis von Suresh, Kaushik, Kundu, Debarati, Ghosh, Sayan, Das, Swagatam, Abraham, Ajith, Han, Sang Yong

“… This paper applies the Differential Evolution (DE) algorithm to the task of automatic fuzzy clustering in a Multi-objective Optimization (MO) framework …”
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RNA-Seq vs Dual- and Single-Channel Microarray Data: Sensitivity Analysis for Differential Expression and Clustering von Sîrbu, Alina, Kerr, Gráinne, Crane, Martin, Ruskin, Heather J.

“… This is based on mRNA sequencing (RNA-seq), which complements the already mature technology of microarrays, and is expected to overcome some of the latter's disadvantages …”
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Categorical data analysis using multiobjective differential evolution based fuzzy clustering von Saha, Indrajit, Maity, Debasree, Maulik, Ujjwal

“… fields of engineering and science. Hence, in this article, Multiobjective Differential Evolution based Fuzzy Clustering for Categorical Data is proposed …”
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Integrated Rough Fuzzy Clustering for Categorical data Analysis von Saha, Indrajit, Sarkar, Jnanendra Prasad, Maulik, Ujjwal

“… In recent times, advanced data mining research has been mostly focusing on clustering of categorical data, where a natural ordering in attribute values is missing …”
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An integrated fuzzy clustering cooperative game data envelopment analysis model with application in hospital efficiency von Omrani, Hashem, Shafaat, Khatereh, Emrouznejad, Ali

“… •To introduce an Integrated Fuzzy Clustering Cooperative Game DEA.•To provide a clustering technique to deal with lack of homogeneity among DMUs …”
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An Integrated Time Series Gene Expression Data Analysis Pipeline with a Fuzzy Clustering method to assess Expression Patterns von Yankilevich, P., Barrero, P.R., Zwir, I.

“… In order to fully explore this type of data we developed an integrated time series gene expression analysis pipeline …”
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AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number von Newman, Aaron M, Cooper, James B

“… Our new method, called AutoSOME, readily identifies discrete and fuzzy data clusters without prior knowledge of cluster number or structure in diverse datasets including whole genome microarray data …”
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Computational Intelligence and Pattern Analysis in Biological Informatics von Sanghamitra Bandyopadhyay, Ujjwal Maulik, Jason T. Wang

“… from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and micro …”
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