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FACTS & FIGURES

JCR Impact Factor: 0.700
JCR 5-Year IF: 0.700
SCOPUS CiteScore: 1.8
Issues per year: 4
Current issue: Nov 2024
Next issue: Feb 2025
Avg review time: 55 days
Avg accept to publ: 60 days
APC: 300 EUR


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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LATEST NEWS

2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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  2/2008 - 8

 HIGHLY CITED PAPER 

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
 
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Click to see author's profile in 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: 1,412 | Views: 5,117

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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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

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 5 [View]
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Updated 3 days ago


Cited-By SCOPUS

SCOPUS® Times Cited: 6
View record in SCOPUS®
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Updated 3 days ago

Cited-By CrossRef

[1] Speech Therapy Based on Expert System, ZAHARIA, M. H., LEON, F., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 9, 2009.
Digital Object Identifier: 10.4316/aece.2009.01014
[CrossRef] [Full text]

[2] Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords, Luque-Baena, R.M., Urda, D., Gonzalo Claros, M., Franco, L., Jerez, J.M., Journal of Biomedical Informatics, ISSN 1532-0464, Issue , 2014.
Digital Object Identifier: 10.1016/j.jbi.2014.01.006
[CrossRef]

[3] An incomplete dominance genetic algorithm approach to microarray data analysis, Melita, Nicolae Teodor, Holban, Stefan, 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), ISBN 978-1-5090-3899-2, 2016.
Digital Object Identifier: 10.1109/ICCP.2016.7737137
[CrossRef]

Updated 3 days ago

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Copyright ©2001-2024
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

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