Open Source Software in Life Science Research

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 Abstract: 1.1 Introduction 1.2 Legacy 1.3 Ambition 1.4 Path chosen 1.5 The 'ilities 1.6 Overall vision 1.7 Lessons learned 1.8 Implementation 1.9 Who uses LSP today? 1.10 Organisation 1.11 Future aspirations Chapter 2: Interactive predictive toxicology with Bioclipse and OpenTox Abstract: 2.1 Introduction 2.2 Basic Bioclipse-OpenTox interaction examples 2.3 Use Case 1: Removing toxicity without interfering with pharmacology 2.4 Use Case 2: Toxicity prediction on compound collections 2.5 Discussion 2.6 Availability Chapter 3: Utilizing open source software to facilitate communication of chemistry at RSC Abstract: 3.1 Introduction 3.2 Project Prospect and open ontologies 3.3 ChemSpider 3.4 ChemDraw Digester 3.5 Learn Chemistry Wiki 3.6 Conclusion 3.7 Acknowledgments 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 Abstract: 5.1 Introduction 5.2 ImageJ 5.3 ImageJ macros: an overview 5.4 Graphical user interface 5.5 Industrial applications of image analysis 5.6 Summary Chapter 6: Integrated data analysis with KNIME Abstract: 6.1 The KNIME platform 6.2 The KNIME success story 6.3 Benefits of 'professional open source' 6.4 Application examples 6.5 Conclusion and outlook 6.6 Acknowledgments Chapter 7: Investigation-Study-Assay, a toolkit for standardizing data capture and sharing Abstract: 7.1 The growing need for content curation in industry 7.2 The BioSharing initiative: cooperating standards needed 7.3 The ISA framework - principles for progress 7.4 Lessons learned 7.5 Acknowledgments Chapter 8: GenomicTools: an open source platform for developing high-throughput analytics in genomics Abstract: 8.1 Introduction 8.2 Data types 8.3 Tools overview 8.4 C++ API for developers 8.5 Case study: a simple ChIP-seq pipeline 8.6 Performance 8.7 Conclusion 8.8 Resources Chapter 9: Creating an in-house âEUR(TM)omics data portal using EBI Atlas software Abstract: 9.1 Introduction 9.2 Leveraging 'omics data for drug discovery 9.3 The EBI Atlas software 9.4 Deploying Atlas in the enterprise 9.5 Conclusion and learnings 9.6 Acknowledgments Chapter 10: Setting up an âEUR(TM)omics platform in a small biotech Abstract: 10.1 Introduction 10.2 General changes over time 10.3 The hardware solution 10.4 Maintenance of the system 10.5 Backups 10.6 Keeping up-to-date 10.7 Disaster recovery 10.8 Personnel skill sets 10.9 Conclusion 10.10 Acknowledgements 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 Abstract: 12.1 Overview 12.2 Methods 12.3 Technical overview 12.4 Infrastructure 12.5 Review 12.6 Acknowledgements Chapter 13: Free and open source software for web-based collaboration Abstract: 13.1 Introduction 13.2 Application of the FLOSS assessment framework 13.3 Conclusion 13.