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High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
Published on: May 21, 2018
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CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets
Åsmund Flobak1, Miguel Vazquez1,2, Astrid Lægreid1
1Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), N-7491 Trondheim, Norway.
Bioinformatics (Oxford, England)
|April 27, 2017
Summary
CImbinator is a new web-service designed for analyzing drug combination screening data. It quantifies drug effects using various mathematical models, aiding in the discovery of beneficial drug synergies.
Area of Science:
- Bioinformatics
- Computational Biology
- Drug Discovery
Background:
- Identifying beneficial drug synergies requires analyzing large datasets.
- User-friendly software is needed for drug combination screening analysis.
Purpose of the Study:
- To develop a web-service for analyzing drug combination screening data.
- To provide tools for both small-scale and large-scale data analysis.
- To quantify drug combination effects using established and advanced models.
Main Methods:
- The CImbinator web-service is implemented in Ruby and R.
- It utilizes the R package drc for advanced dose-response modeling.
- Accessible via web, with open-source code and a Docker image.
Main Results:
- CImbinator facilitates batch-wise and in-depth analysis of drug combination screens.
- It quantifies drug effects using the median effect equation and advanced mathematical models.
- Enables comprehensive analysis of dose-response relationships.
Conclusions:
- CImbinator is a valuable tool for researchers in drug discovery and synergy analysis.
- It supports diverse analytical approaches for drug combination screening data.
- The software enhances the identification of synergistic drug combinations.
