Literature DB >> 17392331

Modeling sequence-sequence interactions for drug response.

Min Lin1, Hongying Li, Wei Hou, Julie A Johnson, Rongling Wu.   

Abstract

MOTIVATION: Genetic interactions or epistasis may play an important role in the genetic etiology of drug response. With the availability of large-scale, high-density single nucleotide polymorphism markers, a great challenge is how to associate haplotype structures and complex drug response through its underlying pharmacodynamic mechanisms.
RESULTS: We have derived a general statistical model for detecting an interactive network of DNA sequence variants that encode pharmacodynamic processes based on the haplotype map constructed by single nucleotide polymorphisms. The model was validated by a pharmacogenetic study for two predominant beta-adrenergic receptor (betaAR) subtypes expressed in the heart, beta1AR and beta2AR. Haplotypes from these two receptors trigger significant interaction effects on the response of heart rate to different dose levels of dobutamine. This model will have implications for pharmacogenetic and pharmacogenomic research and drug discovery. AVAILABILITY: A computer program written in Matlab can be downloaded from the webpage of statistical genetics group at the University of Florida. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2007        PMID: 17392331     DOI: 10.1093/bioinformatics/btm110

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  14 in total

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2.  Using a pharmacokinetic model to relate an individual's susceptibility to alcohol dependence to genotypes.

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Review 4.  A unified mapping framework of multifaceted pharmacodynamic responses to hypertension interventions.

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Journal:  Drug Discov Today       Date:  2019-01-25       Impact factor: 7.851

5.  Detecting maternal-fetal genotype interactions associated with conotruncal heart defects: a haplotype-based analysis with penalized logistic regression.

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Review 6.  Delivering systems pharmacogenomics towards precision medicine through mathematics.

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7.  Stochastic modeling of systems mapping in pharmacogenomics.

Authors:  Zuoheng Wang; Jiangtao Luo; Guifang Fu; Zhong Wang; Rongling Wu
Journal:  Adv Drug Deliv Rev       Date:  2013-03-22       Impact factor: 15.470

8.  Discovering joint associations between disease and gene pairs with a novel similarity test.

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Journal:  BMC Genet       Date:  2010-10-04       Impact factor: 2.797

9.  Functional mapping of genotype-environment interactions for soybean growth by a semiparametric approach.

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10.  A genetic association study detects haplotypes associated with obstructive heart defects.

Authors:  Ming Li; Mario A Cleves; Himel Mallick; Stephen W Erickson; Xinyu Tang; Todd G Nick; Stewart L Macleod; Charlotte A Hobbs
Journal:  Hum Genet       Date:  2014-06-04       Impact factor: 4.132

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