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Fuzzy set-based microarray data analysis techniques for interesting block identification
2009 IEEE International Conference on Fuzzy Systems, 2009Microarrays are one of biotechnology products which enable to measure the expression level of thousands of genes simultaneously. It is sometimes crucial to identify some interesting blocks from microarray data for further investigation. Due to the massive volume of data, it is desirable to get assistance of software tools to handle this task.
Keon-Myung Lee +2 more
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2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA), 2020
Clustering is a very useful machine learning technique to find the underlying classification of unlabeled data. In computational biology, clustering techniques are extensively used to identify a group of biomolecules responsible for biological activity in animals.
Prasad Bandyopadhyay +2 more
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Clustering is a very useful machine learning technique to find the underlying classification of unlabeled data. In computational biology, clustering techniques are extensively used to identify a group of biomolecules responsible for biological activity in animals.
Prasad Bandyopadhyay +2 more
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A multi-objective feature selection and classifier ensemble technique for microarray data analysis
International Journal of Data Mining and Bioinformatics, 2018Since last few years, microarray technology has got tremendous application in many biomedical researches. Many intelligent models have been developed with different biological interpretation. This work presents a multi-objective feature selection and classifier ensemble (MOFSCE) technique for microarray data. MOFSCE works in two phases. The first phase
Rasmita Dash, Bijan Bihari Misra
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Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques
2010 Ninth International Conference on Machine Learning and Applications, 2010One of today’s most important scientific research topics is discovering the genetic links between cancers. This paper contains the results of a comparison of three different cancers (breast, colon, and lung) based on the results of feature selection techniques on a data set created from DNA micro array data consisting of samples from all three cancers.
David J. Dittman +3 more
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Journal of Computational and Theoretical Nanoscience, 2005
Microarrays are among the most powerful tools in biological research, but in order to attain its full potentialities, it is imperative to develop techniques capable to effectively exploit the huge quantity of data which they produce. In this paper two machine learning methodologies for microarray data analysis are proposed: (1) Probabilistic Principal ...
AMATO R. +9 more
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Microarrays are among the most powerful tools in biological research, but in order to attain its full potentialities, it is imperative to develop techniques capable to effectively exploit the huge quantity of data which they produce. In this paper two machine learning methodologies for microarray data analysis are proposed: (1) Probabilistic Principal ...
AMATO R. +9 more
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2006 IEEE International Conference on Systems, Man and Cybernetics, 2006
In this paper we present some performance comparisons of several unsupervised clustering techniques include: Self-Organizing Map (SOM), Fuzzy C-means (FCM) and hierarchical clustering, and they are employed to analyze the ovarian cancer microarray data. The data includes 15 samples with 9,600 genes and these samples include 5 benign ovarian tumors (OVT)
Meng-Hsiun Tsai +3 more
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In this paper we present some performance comparisons of several unsupervised clustering techniques include: Self-Organizing Map (SOM), Fuzzy C-means (FCM) and hierarchical clustering, and they are employed to analyze the ovarian cancer microarray data. The data includes 15 samples with 9,600 genes and these samples include 5 benign ovarian tumors (OVT)
Meng-Hsiun Tsai +3 more
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Impact of Normalization Techniques in Microarray Data Analysis
2023 IEEE Conference on Computer Applications (ICCA), 2023Lwin May Thant, Sabai Phyu
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Microarray and Single Cell Analysis Techniques in Bio-medical Fields
2007Molecular diagnostic technologies will play a significant role in practice of medicine, public health and pharmaceutical industry. Together with genomics and proteomics techniques, the field of pharmacogenomics will develop, with the goal of personalization of diagnosis and therapy, for optimal efficiency and reduced toxicity, contributing to ...
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[Preliminary analysis of gene expression profiles in oral cancer with microarray technique].
Shanghai kou qiang yi xue = Shanghai journal of stomatology, 2004To study the difference in gene expression between oral squamous cell carcinoma tissue and their surrounding normal tissue by microarray so as to investigate the preliminary mechanism of pathogenesis of oral cancer.The tissues from 5 patients with oral squamous cell carcinoma tissue and their surrounding normal tissue from the same patients were ...
Jiang, Tao +4 more
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Soil Science, 2003
Traditional methods for the analysis of soil processes are based on measuring and modeling the distribution of chemical compounds and determining their transformation rates. These approaches have formed the basis of our understanding of soil biogeochemical processes, and they have demonstrated the fundamental role of microbes in regulating these ...
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Traditional methods for the analysis of soil processes are based on measuring and modeling the distribution of chemical compounds and determining their transformation rates. These approaches have formed the basis of our understanding of soil biogeochemical processes, and they have demonstrated the fundamental role of microbes in regulating these ...
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