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

Drug effect prediction by computer.

E E Gloye, R J Marcus

    Science (New York, N.Y.)
    |July 3, 1970
    PubMed
    Summary
    This summary is machine-generated.

    Analyzing extensive drug effect data is challenging. Automated pattern searches reveal new hypotheses about drug mechanisms, aiding scientific discovery.

    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

    Alemtuzumab induction and antibody-mediated rejection in kidney transplantation.

    Transplantation proceedings·2014
    Same author

    Outcomes of paired-exchange live-donor kidney transplantation: a single-center experience.

    Transplantation proceedings·2014
    Same author

    Influence of steroid maintenance on the outcomes in deceased donor kidney transplant recipients experiencing delayed graft function.

    Indian journal of nephrology·2013
    Same author

    Influence of maintenance steroids on the outcomes in deceased-donor kidney transplant recipients exposed to prolonged pretransplantation dialysis.

    Transplantation proceedings·2013
    Same author

    Effect of induction agent on posttransplant outcomes in deceased donor kidney transplant recipients: influence of race.

    Transplantation proceedings·2013
    Same author

    Kidney transplantation in hepatitis C-positive recipients: does type of induction influence outcomes?

    Transplantation proceedings·2012
    Same journal

    Erratum for the Research Article "Detecting supramolecular organic nanoparticles during heat wave".

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

    Local signals, systemic decline.

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

    The mechanics of liver regeneration.

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

    Computing in a memory with physics.

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

    Retraction.

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

    Making time.

    Science (New York, N.Y.)·2026
    See all related articles

    Area of Science:

    • Pharmacology
    • Computational Biology
    • Toxicology

    Background:

    • Vast amounts of data exist on drug effects on biological systems.
    • Traditional analysis methods struggle with this extensive information.

    Purpose of the Study:

    • To develop an automated procedure for analyzing drug effects.
    • To identify patterns in drug-induced behavioral, biochemical, and physiological changes.

    Main Methods:

    • Developed a computerized search procedure for pattern detection.
    • Applied the procedure to a database from The Merck Index.
    • Utilized medical and chemical information for analysis.

    Main Results:

    • Successfully identified patterns in drug effect data.

    Related Experiment Videos

  • Demonstrated the feasibility of automated analysis for large datasets.
  • Generated new hypotheses regarding drug action mechanisms.

    • Conclusions:

    • Automated pattern searching is effective for analyzing complex drug effect data.
    • This approach can lead to novel insights into drug mechanisms.
    • Facilitates hypothesis generation in pharmacology and related fields.