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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: Aug 2017
Next issue: Nov 2017
Avg review time: 105 days


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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FEATURED ARTICLE

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance, ZHANG, Y., WANG, P., CHENG, P., LEI, S.
Issue 3/2017

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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
We have the confirmation Advances in Electrical and Computer Engineering will be included in the Gale database.

2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

Read More »


    
 

  2/2008 - 8

A Genetic Algorithm Approach to DNA Microarrays Analysis of Pancreatic Cancer

MELITA, N. T. See more information about MELITA, N. T. on SCOPUS See more information about MELITA, N. T. on IEEExplore See more information about MELITA, N. T. on Web of Science, POPESCU, I. See more information about  POPESCU, I. on SCOPUS See more information about  POPESCU, I. on SCOPUS See more information about POPESCU, I. on Web of Science, HOLBAN, S. See more information about HOLBAN, S. on SCOPUS See more information about HOLBAN, S. on SCOPUS See more information about HOLBAN, S. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,013 KB) | Citation | Downloads: 927 | Views: 3,038

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
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Full text preview
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.

References Weight

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 2017-10-16 20:42 in 4 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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