Open Source Software in Life Science Research

Practical Solutions to Common Challenges in the Pharmaceutical Industry and Beyond

Edited by

  • Lee Harland, Pfizer
  • Mark Forster, Syngenta, UK

The free/open source approach has grown from a minor activity to become a significant producer of robust, task-orientated software for a wide variety of situations and applications. To life science informatics groups, these systems present an appealing proposition - high quality software at a very attractive price. Open source software in life science research considers how industry and applied research groups have embraced these resources, discussing practical implementations that address real-world business problems.

The book is divided into four parts. Part one looks at laboratory data management and chemical informatics, covering software such as Bioclipse, OpenTox, ImageJ and KNIME. In part two, the focus turns to genomics and bioinformatics tools, with chapters examining GenomicsTools and EBI Atlas software, as well as the practicalities of setting up an ‘omics’ platform and managing large volumes of data. Chapters in part three examine information and knowledge management, covering a range of topics including software for web-based collaboration, open source search and visualisation technologies for scientific business applications, and specific software such as DesignTracker and Utopia Documents. Part four looks at semantic technologies such as Semantic MediaWiki, TripleMap and Chem2Bio2RDF, before part five examines clinical analytics, and validation and regulatory compliance of free/open source software. Finally, the book concludes by looking at future perspectives and the economics and free/open source software in industry.
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Information and informatics processionals across the field of life sciences; Non-IT professionals with a remit concerning business practices and new technologies


Book information

  • Published: October 2012
  • Imprint: Woodhead Publishing
  • ISBN: 978-1-907568-97-8

Table of Contents

Building research data handling systems with open source tools; Interactive predictive toxicology with Bioclipse and OpenTox; Utilizing open source software to facilitate communication of chemistry at RSC; Open source software for mass spectrometry and metabolomics; Open source software for image processing and analysis: Picture this with ImageJ; Integrated data analysis with KNIME; Investigation-Study-Assay, a toolkit for standardizing data capture and sharing; GenomicTools: An open source platform for developing high-throughput analytics in genomics; Creating an in-house ’omics data portal using EBI Atlas software; Setting up an ’omics platform in a small biotech; Squeezing big data into a small organisation; Design Tracker: An easy to use and flexible hypothesis tracking system to aid project team working; Free and open source software for web-based collaboration; Developing scientific business applications using open source search and visualisation technologies; Utopia Documents: Transforming how industrial scientists interact with the scientific literature; Semantic MediaWiki in applied life science and industry: Building an Enterprise Encyclopaedia; Building disease and target knowledge with Semantic MediaWiki; Chem2Bio2RDF: A semantic resource for systems chemical biology and drug discovery; TripleMap: A web-based semantic knowledge discovery and collaboration application for biomedical research; Extreme scale clinical analytics with open source software; Validation and regulatory compliance of free/open source software; The economics of free/open source software in industry.