Galaxy for open-source computational drug discovery solutions

Drug discovery in academia and industry poses contrasting challenges. While academia focuses on producing new knowledge, industry is keen on product development and success in clinical trials. Galaxy is a web-based open-source computational workbench which is used to analyze large datasets and is cu...

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Bibliographic Details
Published in:	Expert opinion on drug discovery Vol. 18; no. 6; p. 579
Main Authors:	Singh Gaur, Anamika, Nagamani, Selvaraman, Priyadarsinee, Lipsa, Mahanta, Hridoy J, Parthasarathi, Ramakrishnan, Sastry, G Narahari
Format:	Journal Article
Language:	English
Published:	England 03-06-2023
Subjects:	Algorithms Computational Biology - methods Drug Discovery Humans Software Workflow drug discovery integrated methods MPDS open-source Data-driven galaxy workflow management system
Online Access:	Get more information
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Summary:	Drug discovery in academia and industry poses contrasting challenges. While academia focuses on producing new knowledge, industry is keen on product development and success in clinical trials. Galaxy is a web-based open-source computational workbench which is used to analyze large datasets and is customized to integrate analysis and visualization tools in a single framework. Depending on the methodology, one can generate customized and suitable workflows in the Galaxy platform. Herein, the authors appraise the suitability of the Galaxy platform for developing a disease specific web portal called the Molecular Property Diagnostic Suite (MPDS). The authors include their future perspectives in the expert opinion section. Galaxy is ideally suited for community-based software development as the scripts, tools, and codes developed in the different programming languages can be integrated in an extremely efficient fashion. MPDS puts forth a new approach known as a disease-specific web portal which aims to implement a range of computational methods and algorithms that can be developed and shared freely across the community of computer aided drug design (CADD) scientists.
ISSN:	1746-045X
DOI:	10.1080/17460441.2023.2205122