Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction

Zeliha Gormez; Olcay Kursun; Ahmet Sertbas; Nizamettin Aydin; Huseyin Seker

doi:10.1109/BHI.2012.6211658

Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction

Zeliha Gormez^*
, Olcay Kursun
, Ahmet Sertbas
, Nizamettin Aydin
, Huseyin Seker

^*Bu çalışma için yazışmadan sorumlu yazar

Istanbul University
Yildiz Technical University
De Montfort University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

2 Atıf (Scopus)

Özet

In exploratory association studies of genes with certain diseases, a single or a small number of genes (features) related with the diseases are selected ¹ among many thousands investigated. We investigate the statistical bias and variance of simple yet common (correlation and mutual information based) feature selection algorithms using well-known cross-validation methods (leave-one-out and k-fold) on a gene finding study for hypertension prediction. Our findings show that selected genes are different for different methods and different cross-validation runs for both single gene selection and gene subset selection.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics
Ana bilgisayar yayını alt yazısı	Global Grand Challenge of Health Informatics, BHI 2012
Sayfalar	616-619
Sayfa sayısı	4
DOI'lar	https://doi.org/10.1109/BHI.2012.6211658
Yayın durumu	Yayınlandı - 2012
Harici olarak yayınlandı	Evet
Etkinlik	IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering - Hong Kong and Shenzhen, China Süre: 2 Oca 2012 → 7 Oca 2012

Yayın serisi

Adı	Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering
Ülke/Bölge	China
Şehir	Hong Kong and Shenzhen
Periyot	2/01/12 → 7/01/12

Belgeye Erişim

10.1109/BHI.2012.6211658

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Gormez, Z., Kursun, O., Sertbas, A., Aydin, N., & Seker, H. (2012). Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction. In Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012 (pp. 616-619). Makale 6211658 (Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012). https://doi.org/10.1109/BHI.2012.6211658

Gormez, Zeliha ; Kursun, Olcay ; Sertbas, Ahmet et al. / Statistical bias and variance of gene selection and cross validation methods : A case study on hypertension prediction. Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. 2012. pp. 616-619 (Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012).

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title = "Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction",

abstract = "In exploratory association studies of genes with certain diseases, a single or a small number of genes (features) related with the diseases are selected 1 among many thousands investigated. We investigate the statistical bias and variance of simple yet common (correlation and mutual information based) feature selection algorithms using well-known cross-validation methods (leave-one-out and k-fold) on a gene finding study for hypertension prediction. Our findings show that selected genes are different for different methods and different cross-validation runs for both single gene selection and gene subset selection.",

author = "Zeliha Gormez and Olcay Kursun and Ahmet Sertbas and Nizamettin Aydin and Huseyin Seker",

year = "2012",

doi = "10.1109/BHI.2012.6211658",

language = "English",

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series = "Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012",

pages = "616--619",

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note = "IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering ; Conference date: 02-01-2012 Through 07-01-2012",

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Gormez, Z, Kursun, O, Sertbas, A, Aydin, N & Seker, H 2012, Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction. in Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012., 6211658, Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012, pp. 616-619, IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering, Hong Kong and Shenzhen, China, 2/01/12. https://doi.org/10.1109/BHI.2012.6211658

Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction. / Gormez, Zeliha; Kursun, Olcay; Sertbas, Ahmet et al.
Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. 2012. p. 616-619 6211658 (Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Statistical bias and variance of gene selection and cross validation methods

T2 - IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health Engineering

AU - Gormez, Zeliha

AU - Kursun, Olcay

AU - Sertbas, Ahmet

AU - Aydin, Nizamettin

AU - Seker, Huseyin

PY - 2012

Y1 - 2012

N2 - In exploratory association studies of genes with certain diseases, a single or a small number of genes (features) related with the diseases are selected 1 among many thousands investigated. We investigate the statistical bias and variance of simple yet common (correlation and mutual information based) feature selection algorithms using well-known cross-validation methods (leave-one-out and k-fold) on a gene finding study for hypertension prediction. Our findings show that selected genes are different for different methods and different cross-validation runs for both single gene selection and gene subset selection.

AB - In exploratory association studies of genes with certain diseases, a single or a small number of genes (features) related with the diseases are selected 1 among many thousands investigated. We investigate the statistical bias and variance of simple yet common (correlation and mutual information based) feature selection algorithms using well-known cross-validation methods (leave-one-out and k-fold) on a gene finding study for hypertension prediction. Our findings show that selected genes are different for different methods and different cross-validation runs for both single gene selection and gene subset selection.

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BT - Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics

Y2 - 2 January 2012 through 7 January 2012

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Gormez Z, Kursun O, Sertbas A, Aydin N, Seker H. Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction. In Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012. 2012. p. 616-619. 6211658. (Proceedings - IEEE-EMBS International Conference on Biomedical and Health Informatics: Global Grand Challenge of Health Informatics, BHI 2012). doi: 10.1109/BHI.2012.6211658

Statistical bias and variance of gene selection and cross validation methods: A case study on hypertension prediction

Özet

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