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Systems-Level Insights into Bronchopulmonary Dysplasia from Meta-Analysis of Genome- Scale Studies
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Pattern Recognition Techniques in Microarray Data Analysis
Annals of the New York Academy of Sciences, 2002Abstract:Recent development of technologies (e.g., microarray technology) that are capable of producing massive amounts of genetic data has highlighted the need for new pattern recognition techniques that can mine and discoverbiologically meaningfulknowledge in large data sets.
Faramarz Valafar
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Analysis of Gene Expression Discretization Techniques in Microarray Biclustering
Lecture Notes in Computer Science, 2017Gene 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.
Ignacio Ponzoni
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A Survey on Filter Techniques for Feature Selection in Gene Expression Microarray Analysis
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012A 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.
Cosmin Lazar +2 more
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Performance analysis of clustering techniques over microarray data: A case study
Physica A: Statistical Mechanics and Its Applications, 2018Abstract 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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Analysis techniques for microarray time-series data
Proceedings of the fifth annual international conference on Computational biology, 2001We address possible limitations of publicly available data sets of yeast gene expression. We study the predictability of known regulators via time-series analysis, and show that less than 20% of known regulatory pairs exhibit strong correlations in the Cho/Spellman data sets.
Vladimir Filkov, Steven Skiena, Jizu Zhi
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A colon cancer microarray analysis technique
2017 E-Health and Bioengineering Conference (EHB), 2017Colon cancer is a very spread malady at international level, symptoms occurring due to a number of vary conditions that may be totally ignored in early stages. Moreover, even treated surgical or with chemotherapy, lots of patients occur recurrence at a specific period of time, so more validated findings in the microarray analysis field, should improve ...
Irina-Oana Petre, Catalin Buiu
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A Microarray Analysis Technique Using a Self-Organizing Multiagent Approach
2021Microarray technology is fully established among the research fields in genetic domain. Academia and industrial researchers investigate and analyze genes' expression to obtain more and more useful information about given organisms, with the aim to perform better disease diagnosis and prediction, accurate medical data analysis, etc.
Forestiero A +3 more
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A novel tissue array technique for high-throughput tissue microarray analysis — microarray groups
In Vitro Cellular & Developmental Biology - Animal, 2007Tissue microarrays are ordered arrays of hundreds to thousands of tissue cores in a single paraffin block. We invented a novel method to make a high-throughput microarray group. Conventional smaller tissue microarrays were made first and then sectioned.
Hui-Yong, Jiang +4 more
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