Skip to main content
Top
Published in: International Journal of Machine Learning and Cybernetics 3/2012

01-09-2012 | Original Article

Improving pattern discovery and visualisation with self-adaptive neural networks through data transformations

Authors: Huiru Zheng, Haiying Wang

Published in: International Journal of Machine Learning and Cybernetics | Issue 3/2012

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The ability to reveal the relevant patterns in an intuitively attractive way through incremental learning makes self-adaptive neural networks (SANNs) a power tool to support pattern discovery and visualisation. Based on the combination of the information related to both the shape and magnitude of the data, this paper introduces a SANN, which implements new similarity matching criteria and error accumulation strategies for network growth. It was tested on two datasets including a real biological gene expression dataset. The results obtained have demonstrated several significant features exhibited by the proposed SANN model for improving pattern discovery and visualisation.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Show more products
Literature
1.
go back to reference Wang JTL, Shapiro BA, Shasha D (1999) Pattern discovery in biomolecular data: tools, techniques, and applications. Oxford University Press, New York Wang JTL, Shapiro BA, Shasha D (1999) Pattern discovery in biomolecular data: tools, techniques, and applications. Oxford University Press, New York
2.
go back to reference Shalizi CR, Crutchfield JP (2000) Pattern discovery and computational mechanics, Santa Fe Insitute Working Paper 00-01-008, Available at: arXiv.org/abs/cs.LG/0001027 Shalizi CR, Crutchfield JP (2000) Pattern discovery and computational mechanics, Santa Fe Insitute Working Paper 00-01-008, Available at: arXiv.org/abs/cs.LG/0001027
3.
go back to reference Pleasance ED, Jones SJM (2005) Evaluation of SAGE tags for Ttranscriptome study. In: Wang SM (ed) SAGE: current technologies and applications, Horizon Scientific Press, Norwich, pp 1–27 Pleasance ED, Jones SJM (2005) Evaluation of SAGE tags for Ttranscriptome study. In: Wang SM (ed) SAGE: current technologies and applications, Horizon Scientific Press, Norwich, pp 1–27
4.
go back to reference Polyak K, Riggins GJ (2001) Gene discovery using the serial analysis of gene expression technique: implications for cancer research. J Clin Oncol 19(11):2948–2958 Polyak K, Riggins GJ (2001) Gene discovery using the serial analysis of gene expression technique: implications for cancer research. J Clin Oncol 19(11):2948–2958
5.
go back to reference Brodlie KW, Carpenter LA, Earnshaw RA, Gallop JR, Hubbard RJ, Mumford AM, Osland CD, Quarendon P (eds) (1992) Scientific visualisation, techniques and applications, Springer, New York Brodlie KW, Carpenter LA, Earnshaw RA, Gallop JR, Hubbard RJ, Mumford AM, Osland CD, Quarendon P (eds) (1992) Scientific visualisation, techniques and applications, Springer, New York
6.
go back to reference Grinstein GG, Ward MO (2002) Introduction to data visualisation. In: Fayyad U, Grinstein GG, Wierse A (eds) Information visualisation in data mining and knowledge discovery, Morgan Kaufmann Publishers, San Francisco, pp 21–45 Grinstein GG, Ward MO (2002) Introduction to data visualisation. In: Fayyad U, Grinstein GG, Wierse A (eds) Information visualisation in data mining and knowledge discovery, Morgan Kaufmann Publishers, San Francisco, pp 21–45
7.
go back to reference Wang HY (2004) Self-Adaptive Neural Network Approaches to Discovering, Visualising and Classifying Patterns in Semi-Structured and Structured Biomedical Data, PhD thesis, University of Ulster Wang HY (2004) Self-Adaptive Neural Network Approaches to Discovering, Visualising and Classifying Patterns in Semi-Structured and Structured Biomedical Data, PhD thesis, University of Ulster
8.
go back to reference Rezende S, Taborelli R, Félix L, Rocha A (1998) Visualisation for knowledge discovery in databases. In: Proceedings of the International Conference on Data Mining (ICDM’98), Rio de Janeiro, Brasil Rezende S, Taborelli R, Félix L, Rocha A (1998) Visualisation for knowledge discovery in databases. In: Proceedings of the International Conference on Data Mining (ICDM’98), Rio de Janeiro, Brasil
11.
go back to reference Alahakoon D, Halgamuge SK, Srinivasan B (2000) Dynamic self-organising maps with controlled growth for knowledge discovery. IEEE Trans Neural Networks 11(3):601–614CrossRef Alahakoon D, Halgamuge SK, Srinivasan B (2000) Dynamic self-organising maps with controlled growth for knowledge discovery. IEEE Trans Neural Networks 11(3):601–614CrossRef
12.
go back to reference Wang H, Azuaje F, Black N (2004) An integrated and interactive framework for improving biomedical pattern discovery and visualization. IEEE Trans Inform Technol Biomed 8(1):16–27CrossRef Wang H, Azuaje F, Black N (2004) An integrated and interactive framework for improving biomedical pattern discovery and visualization. IEEE Trans Inform Technol Biomed 8(1):16–27CrossRef
13.
go back to reference Fritzke B (1994) Growing cell structure–a self-organising network for unsupervised and supervised learning. Neural Netw 7:1441–1460CrossRef Fritzke B (1994) Growing cell structure–a self-organising network for unsupervised and supervised learning. Neural Netw 7:1441–1460CrossRef
14.
go back to reference Herrero J, Valencia A, Dopazo J (2001) A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics 17:126–136CrossRef Herrero J, Valencia A, Dopazo J (2001) A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics 17:126–136CrossRef
15.
go back to reference Kim K, Zhang S, Jiang K, Cai L, Lee I, Feldman L, Huang H (2007) Measuring similarities between gene expression profiles through new data transformations. BMC Bioinform 8:29 Kim K, Zhang S, Jiang K, Cai L, Lee I, Feldman L, Huang H (2007) Measuring similarities between gene expression profiles through new data transformations. BMC Bioinform 8:29
16.
go back to reference Zheng H, Wang H, Azuaje F (2008) Improving pattern discovery and visualization of SAGE data through poisson-based self-adaptive neural networks, IEEE Trans Inform Technol Biomed 12(4), pp 459–469 Zheng H, Wang H, Azuaje F (2008) Improving pattern discovery and visualization of SAGE data through poisson-based self-adaptive neural networks, IEEE Trans Inform Technol Biomed 12(4), pp 459–469
17.
go back to reference Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander E, Golub T (1999) Interpreting patterns of gene expression with self-organising maps: methods and application to hematopoietic differentiation. In: Proc Natl Acad Sci USA 96:2907–2912 Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, Lander E, Golub T (1999) Interpreting patterns of gene expression with self-organising maps: methods and application to hematopoietic differentiation. In: Proc Natl Acad Sci USA 96:2907–2912
18.
go back to reference Fisher RA (1936) The use of multiple measurements in taxonomic problems. Annals of Eugenics VII:179–188 Fisher RA (1936) The use of multiple measurements in taxonomic problems. Annals of Eugenics VII:179–188
19.
go back to reference Blackshaw S, Harpavat S, Trimarchi J, Cai L, Huang H, Kuo W, Lee K, Fraioli R, Cho S, Yung R, Asch E, Wong W, Ohno-Machado L, Weber G, Cepko CL (2004) Genomic analysis of mouse retinal development. PLoS Biol 2(9) Blackshaw S, Harpavat S, Trimarchi J, Cai L, Huang H, Kuo W, Lee K, Fraioli R, Cho S, Yung R, Asch E, Wong W, Ohno-Machado L, Weber G, Cepko CL (2004) Genomic analysis of mouse retinal development. PLoS Biol 2(9)
20.
go back to reference Cai L, Huang H, Blackshaw S, Liu JS, Cepko C, Wong W (2004) Clustering analysis of SAGE data: a Poisson approach. Genome Biol 5:R51 Cai L, Huang H, Blackshaw S, Liu JS, Cepko C, Wong W (2004) Clustering analysis of SAGE data: a Poisson approach. Genome Biol 5:R51
21.
go back to reference Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM (1999) “Systematic determination of genetic network architecture.” Nat Genet 22:281–285 Tavazoie S, Hughes JD, Campbell MJ, Cho RJ, Church GM (1999) “Systematic determination of genetic network architecture.” Nat Genet 22:281–285
22.
go back to reference Reed R (1993) “Pruning algorithms—a survey”. IEEE Trans Neural Netw 4(5):740–747CrossRef Reed R (1993) “Pruning algorithms—a survey”. IEEE Trans Neural Netw 4(5):740–747CrossRef
23.
go back to reference Velculescu VE, Zhang L, Vogelstein B, Kinzler KW (1997) “Serial analysis of gene expression”. Science 276:1268–1272CrossRef Velculescu VE, Zhang L, Vogelstein B, Kinzler KW (1997) “Serial analysis of gene expression”. Science 276:1268–1272CrossRef
24.
go back to reference Grossberg S (1976) “Adaptive pattern classification and universal recoding: I. parallel development and coding of neural feature detectors”. Biol Cybern 23:121–134MathSciNetMATHCrossRef Grossberg S (1976) “Adaptive pattern classification and universal recoding: I. parallel development and coding of neural feature detectors”. Biol Cybern 23:121–134MathSciNetMATHCrossRef
Metadata
Title
Improving pattern discovery and visualisation with self-adaptive neural networks through data transformations
Authors
Huiru Zheng
Haiying Wang
Publication date
01-09-2012
Publisher
Springer-Verlag
Published in
International Journal of Machine Learning and Cybernetics / Issue 3/2012
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-011-0050-z

Other articles of this Issue 3/2012

International Journal of Machine Learning and Cybernetics 3/2012 Go to the issue