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

Genetic sequence data for pharmacogenomics.

Russ B Altman1

  • 1Stanford Medical Informatics, Department of Genetics, 251 Campus Drive MSOB X-215, Stanford, CA 94305-5479, USA. russ.altman@stanford.edu

Current Opinion in Drug Discovery & Development
|July 2, 2003
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

TikTok is a valuable data source for tracking the opioid crisis.

NPJ digital medicine·2026
Same author

Drug-Target Interaction Prediction with PIGLET.

bioRxiv : the preprint server for biology·2026
Same author

GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.

bioRxiv : the preprint server for biology·2026
Same author

Biological data governance in an age of AI.

Science (New York, N.Y.)·2026
Same author

The Human Omnibus of Targetable Pockets.

Journal of cheminformatics·2025
Same author

Publisher Correction: CRISPR-GPT for agentic automation of gene-editing experiments.

Nature biomedical engineering·2025
Same journal

Microreactors for continuous processing – How close to commercial utility?

Current opinion in drug discovery & development·2010
Same journal

Synthesis of polyketide natural products and analogs as promising anticancer agents.

Current opinion in drug discovery & development·2010
Same journal

Enantioselective synthesis of substituted oxindoles and spirooxindoles with applications in drug discovery.

Current opinion in drug discovery & development·2010
Same journal

Eliminating pharmaceutical impurities: Recent advances in detection techniques.

Current opinion in drug discovery & development·2010
Same journal

Stereoselective heterocycle synthesis through oxidative carbon-hydrogen bond activation.

Current opinion in drug discovery & development·2010
Same journal

Catalysis in aqueous media for the synthesis of drug-like molecules.

Current opinion in drug discovery & development·2010
See all related articles

Pharmacogenetics studies how gene variations affect drug responses. Pharmacogenomics uses large-scale genomic data, like DNA sequencing, to identify these variations in important drug-related genes.

Area of Science:

  • Genomics
  • Pharmacology
  • Genetics

Background:

  • Pharmacogenetics investigates genetic influences on drug efficacy and toxicity.
  • Pharmacogenomics applies large-scale genomic techniques to pharmacogenetics.
  • High-throughput DNA sequencing is central to identifying genetic variations.

Purpose of the Study:

  • To outline the scope and methods of pharmacogenomics.
  • To highlight the importance of genetic variations in drug response.
  • To establish baseline measurements of sequence variation in pharmacologically relevant genes.

Main Methods:

  • Utilizing high-throughput DNA sequencing.
  • Conducting systematic surveys of genetic variation.
  • Analyzing coding and promoter regions of genes.

Related Experiment Videos

Main Results:

  • Identification of sequence variations in pharmacologically important genes.
  • Establishment of reliable baseline measurements for genetic variation.
  • Foundation laid for population frequency determination and association studies.

Conclusions:

  • Pharmacogenomics is advancing the understanding of genotype-phenotype relationships in drug response.
  • Systematic genetic variation surveys are crucial for personalized medicine.
  • Future research will focus on linking genetic data to clinical drug outcomes.