Results 251 to 260 of about 89,130 (269)

A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012
A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics.
Lazar, Cosmin, Taminau, Jonatan, Meganck, Stijn, Steenhoff, David, Nowe, Ann, Coletta, Alain, Molter, Colin, De Schaetzen, Virginie, Duque, Robin, Bersini, Hugues   +9 more
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Analysis of Gene Expression Discretization Techniques in Microarray Biclustering

2017
Gene expression biclustering analysis is a commonly used technique to see the interaction between genes under certain experiments or conditions. More specifically in the study of diseases, these methods are used to compare control and affected data in order to identify the involved or relevant genes.
J. S. Dussaut, C. A. Gallo, J. A. Carballido, I. Ponzoni   +3 more
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Performance analysis of clustering techniques over microarray data: A case study

Physica A: Statistical Mechanics and its Applications, 2018
Abstract Handling big data is one of the major issues in the field of statistical data analysis. In such investigation cluster analysis plays a vital role to deal with the large scale data. There are many clustering techniques with different cluster analysis approach. But which approach suits a particular dataset is difficult to predict. To deal with
Rasmita Dash, Bijan Bihari Misra
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A Survey of Classification Techniques for Microarray Data Analysis

2011
With the recent advance of biomedical technology, a lot of ‘OMIC’ data from genomic, transcriptomic, and proteomic domain can now be collected quickly and cheaply. One such technology is the microarray technology which allows researchers to gather information on expressions of thousands of genes all at the same time.
Wai-Ki Yip, Samir B. Amin, Cheng Li
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Similarity analysis of feature ranking techniques on imbalanced DNA microarray datasets

2012 IEEE International Conference on Bioinformatics and Biomedicine, 2012
DNA microarrays are a modern advancement in the analysis of genetic data. This technology allows a researcher to test samples for thousands of genes simultaneously. However, once the samples in the DNA microarrays have been tested, the researcher must then search through the data collected and identify genes important to their problem.
David Dittman, Taghi Khoshgoftaar, Randall Wald, Amri Napolitano   +3 more
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An improved SOM-based visualization technique for DNA microarray data analysis

The 2010 International Joint Conference on Neural Networks (IJCNN), 2010
Effective and meaningful visualization techniques are quite important for multidimensional DNA microarray gene expression data analysis. Elucidating the cluster properties of these multidimensional data are often complex. Patterns, hypotheses on the relationships, and ultimately of the function of the gene can be analyzed and visualized by non-linear ...
Jagdish C. Patra, Jacob Abraham, Pramod K. Meher, Goutam Chakraborty   +3 more
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Performance Comparisons between Unsupervised Clustering Techniques for Microarray Data Analysis on Ovarian Cancer

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, Ching-Hao Lai, Shin-Jr Lu, Shun-Feng Su   +3 more
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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, 2010
One 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, Taghi M. Khoshgoftaar, Randall Wald, Jason Van Hulse   +3 more
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Impact of Normalization Techniques in Microarray Data Analysis

2023 IEEE Conference on Computer Applications (ICCA), 2023
Lwin May Thant, Sabai Phyu
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mRNA Expression Analysis and Classification of Colonic Biopsy Samples Using Oligonucleotide and cDNA Microarray Techniques

Hungarian Medical Journal, 2008
A vastagbéldaganatok korai diagnosztikája, terápiája, követése napjainkban sem teljesen megoldott. Munkánk során a vastagbéldaganatok biomarker-vizsgálatát, génexpressziós elemzését és osztályozását végeztük. Munkacsoportunk vizsgálatai alapján megállapítható, hogy a biopsziás minták oligonukleotid microarray-vizsgálati módszere az Affymetrix minőségi ...
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