Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Modeling sequence-sequence interactions for drug response.

Min Lin1, Hongying Li, Wei Hou

  • 1Department of Statistics, University of Florida, Gainesville, FL 32611, USA.

Bioinformatics (Oxford, England)
|March 30, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

GZMB<sup>+</sup>CD4<sup>+</sup>CD8<sup>+</sup> T cells in rheumatoid arthritis: a potential therapeutic target for IL-27 intervention.

Journal of translational medicine·2026
Same author

ICD-11 pilot in West China: feasibility evaluation and implications for future implementation.

Scientific reports·2026
Same author

Correction: Premature renal epithelial cell senescence promoted by LXN/Rps3/p53 signaling pathway activation increases calcium oxalate crystal deposition by altering macrophage polarization.

Frontiers in immunology·2026
Same author

Polysaccharide-based anticancer therapeutics: molecular mechanisms, translational advances, and the road toward precision oncology.

Frontiers in pharmacology·2026
Same author

Carboxymethyl chitosan and daptomycin stabilized AgPt nanozymes with excellent peroxidase-like activity for uricase-free colorimetric detection of uric acid.

International journal of biological macromolecules·2026
Same author

Effect of DL-3-n-Butylphthalide on Cerebral Hypoperfusion Due to Atherosclerotic Stenosis: A Multicenter, Double-Blind, Randomized Controlled, Preliminary Trial.

CNS drugs·2026
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

This study introduces a new statistical model to uncover genetic interactions influencing drug response by analyzing DNA sequence variants and their pharmacodynamic effects. The model successfully identified interactions between beta-adrenergic receptor genes affecting heart rate response to dobutamine.

Area of Science:

  • Pharmacogenetics
  • Statistical Genetics
  • Computational Biology

Background:

  • Genetic interactions (epistasis) are crucial for understanding drug response variations.
  • High-density single nucleotide polymorphism (SNP) markers present challenges in associating haplotype structures with complex drug responses via pharmacodynamics.

Purpose of the Study:

  • To develop a general statistical model for detecting interactive networks of DNA sequence variants involved in pharmacodynamic processes.
  • To validate the model using a pharmacogenetic study of beta-adrenergic receptor (betaAR) subtypes.

Main Methods:

  • Developed a statistical model utilizing haplotype maps constructed from SNPs.
  • Applied the model to analyze genetic interactions of beta1AR and beta2AR in a pharmacogenetic study.

Related Experiment Videos

  • Investigated the effects of receptor haplotypes on heart rate response to dobutamine.

    • Main Results:

    • The derived statistical model effectively detects interactive networks of DNA variants encoding pharmacodynamic processes.
    • Significant interaction effects were found between beta1AR and beta2AR haplotypes on heart rate response to dobutamine.
    • The model provides a robust framework for analyzing complex genetic influences on drug response.

    Conclusions:

    • The developed model offers a powerful tool for pharmacogenetic and pharmacogenomic research.
    • This approach has implications for identifying novel drug targets and advancing personalized medicine.
    • The study highlights the importance of considering genetic interactions in drug response.