Data Mining in Complex Diseases Using Evolutionary Computation

Vanessa Aguiar; Jose A. Seoane; Ana Freire; Cristian R. Munteanu

Data Mining in Complex Diseases Using Evolutionary Computation

Vanessa Aguiar, Jose A. Seoane, Ana Freire, Cristian R. Munteanu

Bristol Medical School (PHS)

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

6 Citations (Scopus)

Abstract

A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. fit this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time oil real data.

Original language	English
Title of host publication	BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1
Editors	J Cabestany, A Prieto, F Sandoval, JM Corchado
Place of Publication	BERLIN
Publisher	Springer-Verlag Berlin
Pages	917-924
Number of pages	8
ISBN (Print)	978-3-642-02477-1
Publication status	Published - 2009
Event	10th International Work-Conference on Artificial Neural Networks (IWANN 2009) - Salamanca, Spain Duration: 10 Jun 2009 → 12 Jun 2009

Conference

Conference	10th International Work-Conference on Artificial Neural Networks (IWANN 2009)
Country/Territory	Spain
City	Salamanca
Period	10/06/09 → 12/06/09

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@inproceedings{e9f6b683c128498495e86a5f72fa4a20,

title = "Data Mining in Complex Diseases Using Evolutionary Computation",

abstract = "A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. fit this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time oil real data.",

author = "Vanessa Aguiar and Seoane, {Jose A.} and Ana Freire and Munteanu, {Cristian R.}",

year = "2009",

language = "English",

isbn = "978-3-642-02477-1",

pages = "917--924",

editor = "J Cabestany and A Prieto and F Sandoval and JM Corchado",

booktitle = "BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1",

publisher = "Springer-Verlag Berlin",

note = "10th International Work-Conference on Artificial Neural Networks (IWANN 2009) ; Conference date: 10-06-2009 Through 12-06-2009",

}

Aguiar, V, Seoane, JA, Freire, A & Munteanu, CR 2009, Data Mining in Complex Diseases Using Evolutionary Computation. in J Cabestany, A Prieto, F Sandoval & JM Corchado (eds), BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1. Springer-Verlag Berlin, BERLIN, pp. 917-924, 10th International Work-Conference on Artificial Neural Networks (IWANN 2009), Salamanca, Spain, 10/06/09.

Data Mining in Complex Diseases Using Evolutionary Computation. / Aguiar, Vanessa; Seoane, Jose A.; Freire, Ana et al.

BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1. ed. / J Cabestany; A Prieto; F Sandoval; JM Corchado. BERLIN : Springer-Verlag Berlin, 2009. p. 917-924.

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Data Mining in Complex Diseases Using Evolutionary Computation

AU - Aguiar, Vanessa

AU - Seoane, Jose A.

AU - Freire, Ana

AU - Munteanu, Cristian R.

PY - 2009

Y1 - 2009

N2 - A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. fit this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time oil real data.

AB - A new algorithm is presented for finding genotype-phenotype association rules from data related to complex diseases. The algorithm was based on Genetic Algorithms, a technique of Evolutionary Computation. The algorithm was compared to several traditional data mining techniques and it was proved that it obtained similar classification scores but found more rules from the data generated artificially. fit this paper it is assumed that several groups of SNPs have an impact on the predisposition to develop a complex disease like schizophrenia. It is expected to validate this in a short period of time oil real data.

M3 - Conference Contribution (Conference Proceeding)

SN - 978-3-642-02477-1

SP - 917

EP - 924

BT - BIO-INSPIRED SYSTEMS: COMPUTATIONAL AND AMBIENT INTELLIGENCE, PT 1

A2 - Cabestany, J

A2 - Prieto, A

A2 - Sandoval, F

A2 - Corchado, JM

PB - Springer-Verlag Berlin

CY - BERLIN

T2 - 10th International Work-Conference on Artificial Neural Networks (IWANN 2009)

Y2 - 10 June 2009 through 12 June 2009

ER -

Data Mining in Complex Diseases Using Evolutionary Computation

Abstract

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