Selecting SNPs for pharmacogenomic association study

Tae Jin Ahn; Kyunghee Park; Dae Soon Son; Nam Huh; Sohee Oh; Taejung Bae; Jung Sun Park; Ji Hyun Lee; Kyoohyoung Rho; Sunghoon Kim; Taesung Park; Kyusang Lee

doi:10.1504/IJDMB.2012.049317

Selecting SNPs for pharmacogenomic association study

Tae Jin Ahn, Kyunghee Park, Dae Soon Son, Nam Huh, Sohee Oh, Taejung Bae, Jung Sun Park, Ji Hyun Lee, Kyoohyoung Rho, Sunghoon Kim, Taesung Park, Kyusang Lee

Department of Pharmacy

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

SNP genotyping device is an essential tool in the upcoming era of personal genome and personalised medicine. Human genome has more than 10 million SNPs whereas conventional SNP genotyping device can only hold 1 million SNPs. Thus, intelligent SNP contents selection is required to maximise the value of SNP genotyping device. Here, we developed a new selection algorithm and applied this method to design genotyping contents for cancer and pharmacogenomic association study. This approach signifi cantly increased the product value when compared with contents of competitive SNP genotyping product.

Original language	English
Pages (from-to)	521-533
Number of pages	13
Journal	International Journal of Data Mining and Bioinformatics
Volume	6
Issue number	5
DOIs	https://doi.org/10.1504/IJDMB.2012.049317
Publication status	Published - 2012 Sep

All Science Journal Classification (ASJC) codes

Information Systems
Biochemistry, Genetics and Molecular Biology(all)
Library and Information Sciences

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1504/IJDMB.2012.049317

Cite this

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title = "Selecting SNPs for pharmacogenomic association study",

abstract = "SNP genotyping device is an essential tool in the upcoming era of personal genome and personalised medicine. Human genome has more than 10 million SNPs whereas conventional SNP genotyping device can only hold 1 million SNPs. Thus, intelligent SNP contents selection is required to maximise the value of SNP genotyping device. Here, we developed a new selection algorithm and applied this method to design genotyping contents for cancer and pharmacogenomic association study. This approach signifi cantly increased the product value when compared with contents of competitive SNP genotyping product.",

author = "Ahn, {Tae Jin} and Kyunghee Park and Son, {Dae Soon} and Nam Huh and Sohee Oh and Taejung Bae and Park, {Jung Sun} and Lee, {Ji Hyun} and Kyoohyoung Rho and Sunghoon Kim and Taesung Park and Kyusang Lee",

year = "2012",

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doi = "10.1504/IJDMB.2012.049317",

language = "English",

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journal = "International Journal of Data Mining and Bioinformatics",

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Selecting SNPs for pharmacogenomic association study. / Ahn, Tae Jin; Park, Kyunghee; Son, Dae Soon; Huh, Nam; Oh, Sohee; Bae, Taejung; Park, Jung Sun; Lee, Ji Hyun; Rho, Kyoohyoung; Kim, Sunghoon; Park, Taesung; Lee, Kyusang.

In: International Journal of Data Mining and Bioinformatics, Vol. 6, No. 5, 09.2012, p. 521-533.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Selecting SNPs for pharmacogenomic association study

AU - Ahn, Tae Jin

AU - Park, Kyunghee

AU - Son, Dae Soon

AU - Huh, Nam

AU - Oh, Sohee

AU - Bae, Taejung

AU - Park, Jung Sun

AU - Lee, Ji Hyun

AU - Rho, Kyoohyoung

AU - Kim, Sunghoon

AU - Park, Taesung

AU - Lee, Kyusang

PY - 2012/9

Y1 - 2012/9

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AB - SNP genotyping device is an essential tool in the upcoming era of personal genome and personalised medicine. Human genome has more than 10 million SNPs whereas conventional SNP genotyping device can only hold 1 million SNPs. Thus, intelligent SNP contents selection is required to maximise the value of SNP genotyping device. Here, we developed a new selection algorithm and applied this method to design genotyping contents for cancer and pharmacogenomic association study. This approach signifi cantly increased the product value when compared with contents of competitive SNP genotyping product.

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Selecting SNPs for pharmacogenomic association study

Abstract

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