Results 221 to 230 of about 180,353 (259)

Genome-Wide Analysis of Pancreatic Cancer Using Microarray-Based Techniques

Pancreatology, 2009
Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes.We analysed a total
Claude Chelala, Tatjana Crnogorac-Jurcevic, Nicholas R. Lemoine, Tomohiko Harada   +3 more
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Single Nucleotide Polymorphism Analysis in HIV and Kaposi's Sarcoma Disease by Microarray Technique

Current HIV Research, 2020
Background: Emergence of Kaposi's Sarcoma in the cases other than HIV, following the use of immunosuppressant drugs, demonstrates that it is related to weak immunity. The fact that this malignancy does not occur in every HIV-positive patient suggests that genetic predisposition may also be effective.
Ismail Koyuncu, Ataman Gönel, Emrah Ozcan, Ebru Temiz, Şahin Toprak, Feridun Akkafa, Irfan Binici   +6 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.
Cristian Andrés Gallo, Julieta Sol Dussaut, Ignacio Ponzoni, Jessica Andrea Carballido   +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
Bijan Bihari Misra, Rasmita Dash
openaire   +2 more sources

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.
Randall Wald, Taghi M. Khoshgoftaar, Amri Napolitano, David J. Dittman   +3 more
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The optimized adaptive density estimation technique applied to microarray data analysis

2014 International Conference on Multimedia Computing and Systems (ICMCS), 2014
This paper describes and proposes a method of optimizing the smoothing parameter of an estimator of the probability density function (PDF) called the adaptive kernel estimator (AKE). This optimized estimator is used to build the Bayes classifier in the classification of microarray data. The study profiles and gene expression have made great advances in
Yissam Lakhdar, El Hassan Sbai
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Novel Techniques for Microarray Data Analysis: Probabilistic Principal Surfaces and Competitive Evolution on Data

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., CIARAMELLA A., DEL MONDO C., DE VINCO L., DONALEK C., LONGO, GIUSEPPE, MIELE, GENNARO, RAICONI G., STAIANO A., TAGLIAFERRI R.   +9 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 ...
Pramod Kumar Meher, Goutam Chakraborty, Jacob Abraham, Jagdish C. Patra   +3 more
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Performance Analysis of Microarray Data Classification using Machine Learning Techniques

International Journal of Knowledge Discovery in Bioinformatics, 2015
Microarray technology of DNA permits simultaneous monitoring and determining of thousands of gene expression activation levels in a single experiment. Data mining technique such as classification is extensively used on microarray data for medical diagnosis and gene analysis.
Ajay Kumar Mishra, Subhendu Kumar Pani, Bikram Kesari Ratha   +2 more
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Comparative study on dimension reduction techniques for cluster analysis of microarray data

The 2011 International Joint Conference on Neural Networks, 2011
This paper proposes a study on the impact of the use of dimension reduction techniques (DRTs) in the quality of partitions produced by cluster analysis of microarray datasets. We tested seven DRTs applied to four microarray cancer datasets and ran four clustering algorithms using the original and reduced datasets. Overall results showed that using DRTs
Daniel Araújo, Adrião Duarte Dória Neto, Jorge Dantas de Melo, Allan de Medeiros Martins   +3 more
openaire   +2 more sources