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Updated: Apr 20, 2026

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Published on: December 11, 2016
Drug discovery FAQs: workflows for answering multidomain drug discovery questions
Christine Chichester1, Daniela Digles2, Ronald Siebes3
1Swiss Institute of Bioinformatics, CALIPHO Group, CMU, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.
The Open PHACTS Discovery Platform integrates compound, target, pathway, and disease data to answer key pharmaceutical industry questions. Workflows are available to support computational drug discovery and accelerate research.
Area of Science:
- Computational chemistry
- Bioinformatics
- Drug discovery
Background:
- Data-driven drug discovery necessitates integrated resources for informed decision-making.
- The pharmaceutical industry faces high-priority questions regarding compound, target, pathway, and disease data integration.
- Existing resources often lack comprehensive integration for complex drug discovery queries.
Purpose of the Study:
- To introduce the Open PHACTS Discovery Platform as a solution for integrated drug discovery data.
- To demonstrate the utility of computational workflows for addressing key drug discovery questions.
- To provide accessible and reusable workflows for the scientific community.
Main Methods:
- Development of the Open PHACTS Discovery Platform, integrating diverse biological and chemical data.
- Creation of computational drug discovery workflows addressing frequently asked questions (FAQs).
- Utilizing workflow tools for data analysis and kết quả interpretation.
Main Results:
- The Open PHACTS platform effectively integrates data on compounds, targets, pathways, and diseases.
- Selected workflows successfully address high-priority drug discovery use cases.
- Workflows are published on myExperiment for community access and reuse.
Conclusions:
- Integrated data resources and computational workflows are crucial for modern drug discovery.
- The Open PHACTS platform and its associated workflows offer valuable tools for researchers.
- Continued development and community engagement are vital for advancing computational drug discovery.
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