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 Concept Videos

Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Pharmacogenetics and Pharmacogenomics: Overview01:29

Pharmacogenetics and Pharmacogenomics: Overview

Pharmacogenetics and pharmacogenomics examine how genetic factors influence an individual's response to drugs. While pharmacogenetics focuses on the impact of specific genetic variants on drug effects, pharmacogenomics takes a broader approach, studying how genetic variation across populations contributes to differences in drug responses. These fields aim to explain why individuals may experience varying levels of efficacy or adverse reactions to the same medication.Variability in drug...
Combined Effects of Drugs: Synergism01:27

Combined Effects of Drugs: Synergism

Synergism is a useful mechanism where combining two or more drugs is more effective than each constituent used alone. Such combinations are also called supra-additive interactions. The drugs collectively enhance the final therapeutic effect by acting on different targets. Another advantage is that the low dose of each constituent drug is sufficient to achieve the desired effect. This helps reduce the duration of therapy and lower the adverse effects of these drugs.
Such synergistic combinations...
Drug toxicity: Drug–Drug Interaction01:30

Drug toxicity: Drug–Drug Interaction

Drug–drug interactions can precipitate toxicity through multiple mechanisms. Absorption interactions alter how drugs enter the body, exemplified when ranitidine increases the absorption of basic drugs, while cholestyramine decreases the levels of propranolol. Protein binding interactions occur when drugs share the same binding sites on plasma proteins. Drugs like aspirin and warfarin, when bound in excess, can lead to increased free drug concentrations, enhancing the potential for...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

You might also read

Related Articles

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

Sort by
Same author

Comprehensive review and assessment of multi-species splicing variant prediction: task-specific deep learning models and genomic foundation models.

Briefings in bioinformatics·2026
Same author

EIGNN: An Explainable Imaging-Genetic Neural Network for Robust Alzheimer's Disease Risk Prediction.

IEEE transactions on medical imaging·2026
Same author

Deciphering cell type-specific causal genetic effects on brain imaging-derived phenotypes and disorders with single-cell Mendelian randomization.

PLoS computational biology·2026
Same author

A synthetic protein plug for assembly of bio-nano-hybrids with direct electron transfer powered photobiocatalysis.

Chemical communications (Cambridge, England)·2026
Same author

Genetic contributors to postoperative delirium and their implications for dementia outcomes.

Anesthesiology·2026
Same author

Corrigendum to "Identification of a novel antimicrobial peptide Gp-AMP1 with broad-spectrum and exceptional stability from deep-sea mussel Gigantidas platifrons" [Food Chem. 501 (2026) 147576].

Food chemistry·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: May 22, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

Exploring drug combinations in genetic interaction network.

Yin-Ying Wang1, Ke-Jia Xu, Jiangning Song

  • 1Institute of Systems Biology, Shanghai University, Shanghai 200444, China.

BMC Bioinformatics
|May 19, 2012
PubMed
Summary
This summary is machine-generated.

Identifying effective drug combinations is challenging. This study uses network biology to reveal that successful drug combinations target related pathways and have a smaller effect radius in genetic interaction networks.

More Related Videos

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
07:51

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Published on: May 21, 2018

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Related Experiment Videos

Last Updated: May 22, 2026

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
07:40

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions

Published on: May 27, 2021

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
07:51

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Published on: May 21, 2018

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Area of Science:

  • Computational Biology
  • Systems Biology
  • Pharmacology

Background:

  • Drug combinations offer improved therapeutic effects for complex diseases.
  • Identifying effective drug combinations is challenging due to the vast number of possibilities.
  • Molecular context is crucial for understanding drug combination mechanisms.

Purpose of the Study:

  • To investigate drug combinations and their targets using network biology.
  • To understand the underlying rules of effective drug combinations.
  • To analyze drug combinations within genetic interaction networks and human pathways.

Main Methods:

  • Network biology approach
  • Analysis of genetic interaction networks
  • Integration with human pathways

Main Results:

  • Combinatorial drugs exhibit a smaller effect radius in genetic interaction networks.
  • Drug combinations are more likely to modulate functionally related pathways.
  • Network properties provide insights into therapeutic effects.

Conclusions:

  • Molecular networks offer critical insights into effective drug combination strategies.
  • Findings can accelerate the discovery of novel drug combinations.
  • Network-based analysis is valuable for drug combination research.