OPTIMIZATION OF SUPERVISED SELF-ORGANIZING MAPS WITH GENETIC ALGORITHMS FOR CLASSIFICATION ELECTROPHORETIC PROFILES

被引：1

作者：

Tomovska, Natalija ^{[1
]}

Kuzmanovski, Igor ^{[1
]}

Stojanoski, Kiro ^{[1
]}

机构：

[1] Ss Cyril & Methodius Univ, Fac Nat Sci & Math, Inst Chem, Skopje, Macedonia

来源：

MACEDONIAN JOURNAL OF CHEMISTRY AND CHEMICAL ENGINEERING | 2014年 / 33卷 / 01期

关键词：

disc electrophoresis; cerebrospinal fluid; protein analysis; supervised self-organizing maps; ARTIFICIAL NEURAL-NETWORKS; WAVELENGTH SELECTION; MULTIPLE-SCLEROSIS; KOHONEN; SPECTROMETRY; PARTICLES;

D O I：

10.20450/mjcce.2014.436

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Standard electrophoresis methods were used to classify analyzed proteins in cerebrospinal fluid from patients with multiple sclerosis. Disc electrophoresis was carried out on polyacrylamide gels for the detection of oligoclonal IgG bands in cerebrospinal fluid, mainly from patients with multiple sclerosis and other central nervous system dysfunctions. ImageMaster 1D Elite and Gel- Pro specialized software packages were used for fast accurate image and gel analysis. The classification model was based on supervised self-organizing maps. In order to perform modeling in an automated manner, genetic algorithms were used. Using this approach and a data set composed of 69 samples, we developed models based on supervised self-organizing maps which were able to correctly classify 83% of the samples in the data set used for external validation.

引用

页码：65 / 71

页数：7

共 50 条

[1] Optimization of supervised self-organizing maps with genetic algorithms for classification of urinary calculi
Kuzmanovski, I
Trpkovska, M
Soptrajanov, B
JOURNAL OF MOLECULAR STRUCTURE, 2005, 744 : 833 - 838
[2] On the optimization of Self-Organizing Maps by Genetic Algorithms
Polani, D
KOHONEN MAPS, 1999, : 157 - 169
[3] Classification of perovskites with supervised self-organizing maps
Kuzmanovski, Igor
Dimitrovska-Lazova, Sandra
Aleksovska, Slobotka
ANALYTICA CHIMICA ACTA, 2007, 595 (1-2) : 182 - 189
[4] Application of self-organizing maps to genetic algorithms
Kan, S.
Fei, Z.
Kita, E.
COMPUTER AIDED OPTIMUM DESIGN IN ENGINEERING XI, 2009, 106 : 3 - 11
[5] Self-Organizing Maps with supervised layer
Platon, Ludovic
Zehraoui, Farida
Tahi, Fariza
2017 12TH INTERNATIONAL WORKSHOP ON SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION, CLUSTERING AND DATA VISUALIZATION (WSOM), 2017, : 161 - 168
[6] Extending self-organizing maps for supervised classification of remotely sensed data
CHEN Yongliang Comprehensive Information Institute of Mineral Resources Prediction
GlobalGeology, 2009, 12 (01) : 46 - 56
[7] EM algorithms for self-organizing maps
Heskes, T
Spanjers, JJ
Wiegerinck, W
IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL VI, 2000, : 9 - 14
[8] Architecture optimization model for the probabilistic self-organizing maps and classification
En-naimani, Z.
Lazaar, M.
Ettaouil, M.
2014 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA'14), 2014,
[9] Additive Composition of Supervised Self-Organizing Maps
Jean-Luc Buessler
Jean-Philippe Urban
Julien Gresser
Neural Processing Letters, 2002, 15 : 9 - 20
[10] Multiple self-organizing maps for supervised learning
Cervera, E
delPobil, AP
FROM NATURAL TO ARTIFICIAL NEURAL COMPUTATION, 1995, 930 : 345 - 352

← 1 2 3 4 5 →