- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of figures and tables
- Foreword
- About the editors
- About the contributors
- Introduction
- Chapter 1: Building research data handling systems with open source tools
- Chapter 2: Interactive predictive toxicology with Bioclipse and OpenTox
- Chapter 3: Utilizing open source software to facilitate communication of chemistry at RSC
- Chapter 4: Open source software for mass spectrometry and metabolomics
- Abstract:
- 4.1 Introduction
- 4.2 A short mass spectrometry primer
- 4.3 Metabolomics and metabonomics
- 4.4 Data types
- 4.5 Metabolomics data processing
- 4.6 Metabolomics data processing using the open source workflow engine, KNIME
- 4.7 Open source software for multivariate analysis
- 4.8 Performing PCA on metabolomics data in R/KNIME
- 4.9 Other open source packages
- 4.10 Perspective
- 4.11 Acknowledgments
- Chapter 5: Open source software for image processing and analysis: picture this with ImageJ
- Chapter 6: Integrated data analysis with KNIME
- Chapter 7: Investigation-Study-Assay, a toolkit for standardizing data capture and sharing
- Chapter 8: GenomicTools: an open source platform for developing high-throughput analytics in genomics
- Chapter 9: Creating an in-house ’omics data portal using EBI Atlas software
- Chapter 10: Setting up an ’omics platform in a small biotech
- Chapter 11: Squeezing big data into a small organisation
- Abstract:
- 11.1 Introduction
- 11.2 Our service and its goals
- 11.3 Manage the data: relieving the burden of data-handling
- 11.4 Organising the data
- 11.5 Standardising to your requirements
- 11.6 Analysing the data: helping users work with their own data
- 11.7 Helping biologists to stick to the rules
- 11.8 Running programs
- 11.9 Helping the user to understand the details
- 11.10 Summary
- Chapter 12: Design Tracker: an easy to use and flexible hypothesis tracking system to aid project team working
- Chapter 13: Free and open source software for web-based collaboration
- Chapter 14: Developing scientific business applications using open source search and visualisation technologies
- Abstract:
- 14.1 A changing attitude
- 14.2 The need to make sense of large amounts of data
- 14.3 Open source search technologies
- 14.4 Creating the foundation layer
- 14.5 Visualisation technologies
- 14.6 Prefuse visualisation toolkit
- 14.7 Business applications
- 14.8 Other applications
- 14.9 Challenges and future developments
- 14.10 Reflections
- 14.11 Thanks and Acknowledgements
- Chapter 15: Utopia Documents: transforming how industrial scientists interact with the scientific literature
- Chapter 16: Semantic MediaWiki in applied life science and industry: building an Enterprise Encyclopaedia
- Chapter 17: Building disease and target knowledge with Semantic MediaWiki
- Chapter 18: Chem2Bio2RDF: a semantic resource for systems chemical biology and drug discovery
- Chapter 19: TripleMap: a web-based semantic knowledge discovery and collaboration application for biomedical research
- Abstract:
- 19.1 The challenge of Big Data
- 19.2 Semantic technologies
- 19.3 Semantic technologies overview
- 19.4 The design and features of TripleMap
- 19.5 TripleMap Generated Entity Master ('GEM') semantic data core
- 19.6 TripleMap semantic search interface
- 19.7 TripleMap collaborative, dynamic knowledge maps
- 19.8 Comparison and integration with third-party systems
- 19.9 Conclusions
- Chapter 20: Extreme scale clinical analytics with open source software
- Chapter 21: Validation and regulatory compliance of free/open source software
- Chapter 22: The economics of free/open source software in industry
- Index
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