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A Genetic Algorithm Approach to DNA Microarrays Analysis of Pancreatic CancerMELITA, N. T. , POPESCU, I. , HOLBAN, S. |
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Author keywords
DNA Microarrays, Feature Selection, Genetic Algorithm, Suppot Vector Machines, Pancreatic Cancer
References keywords
microarray(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2008-06-02
Volume 8, Issue 2, Year 2008, On page(s): 43 - 48
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2008.02008
Web of Science Accession Number: 000264815000008
SCOPUS ID: 67749089529
Abstract
We address the problem of collecting and analyzing vast amount of information in medicine and biology, in the light of the revolutionary technological evolution during the last decades. Currently, the methods of achieving information challenge our capacity to sort and process that data. However, we use the methods of machine learning to sort and analyze this information. In this comprehensive review we describe an experiment of analyzing DNA microarrays using a Genetic Algorithm for feature selection. We study how we can establish a causal relationship between a pattern of genic expression and the evolution of pancreatic cancer using a Genetic Algorithm. |
References | | | Cited By «-- Click to see who has cited this paper |
[1] Helen Causton, John Quackenbush, Alvis Brazma, "Microarray Gene Expression Data Analysis: A Beginner's Guide", Blackwell Publishing Professional, 2003.
[2] Dov Stekel, "Microarray Bioinformatics", Cambridge University Press, 2003. [3] H. Ressom, "Lecture Notes", Georgetown University, 2007. [4] R. O. Duda, P. E. Hart and D. G. Stork, "Pattern Classification", Second Edition, Wiley, 2001. [5] I. Witten and E. Frank, "Data Mining", 2nd Ed., Morgan Kaufmann, 2005. [6] W. N. Venables, D. M. Smith & the R Development Core Team, "An Introduction to R", 2006. [7] William N. Venables and Brian D. Ripley, "Modern Applied Statistics with S", Fourth Edition, Springer, New York, 2002. [8] William N. Venables and Brian D. Ripley, "S Programming", Springer, New York, 2000. [9] D. G. Stork and E. Yom-Tov, "Computer Manual in MATLAB to Accompany Pattern Classification", Second Edition, Wiley, 2004. [10] Sam Roberts, "Using Genetic Algorithms to Select a Subset of Predictive Variables from a High-Dimensional Microarray Dataset", 2005. [11] Nicolae Morariu, Sorin Vlad, "Using Pattern Classification and Recognition Techniques for Diagnostic and Prediction", Advances in Electrical and Computer Engineering, Vol. 7, 2007. [12] Robert Gentleman, Vince Carey, Wolfgang Huber, Rafael A. Irizarry, Sandrine Dudoit, "Bioinformatics and Computational Biology Solutions using R and Bioconductor", Springer, New York, 2005. [13] Smyth, G. K., "Linear models and empirical Bayes methods for assessing dierential expression in microarray experiments", Statistical Applications in Genetics and Molecular Biology, Vol. 3, No. 1, Article 3, 2004. Web of Science® Citations for all references: 0 SCOPUS® Citations for all references: 0 Web of Science® Average Citations per reference: 0 SCOPUS® Average Citations per reference: 0 TCR = Total Citations for References / ACR = Average Citations per Reference We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more Citations for references updated on 2024-11-30 17:56 in 3 seconds. Note1: Web of Science® is a registered trademark of Clarivate Analytics. Note2: SCOPUS® is a registered trademark of Elsevier B.V. Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site. |
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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