Open Source Software in Life Science Research. Woodhead Publishing Series in Biomedicine

Transcription

1 Brochure More information from Open Source Software in Life Science Research. Woodhead Publishing Series in Biomedicine Description: 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 webbased 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. - Discusses a broad range of applications from a variety of sectors - Provides a unique perspective on work normally performed behind closed doors - Highlights the criteria used to compare and assess different approaches to solving problems Contents: 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 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

2 1.9 Who uses LSP today? 1.10 Organisation 1.11 Future aspirations Chapter 2: Interactive predictive toxicology with Bioclipse and OpenTox 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 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 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

3 4.11 Acknowledgments Chapter 5: Open source software for image processing and analysis: picture this with ImageJ 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 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 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 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

4 8.6 Performance 8.7 Conclusion 8.8 Resources Chapter 9: Creating an in-house â?tomics data portal using EBI Atlas software 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 â?tomics platform in a small biotech 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 Acknowledgements Chapter 11: Squeezing big data into a small organisation 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

5 11.7 Helping biologists to stick to the rules 11.8 Running programs 11.9 Helping the user to understand the details Summary Chapter 12: Design Tracker: an easy to use and flexible hypothesis tracking system to aid project team working 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 13.1 Introduction 13.2 Application of the FLOSS assessment framework 13.3 Conclusion 13.4 Acknowledgements Chapter 14: Developing scientific business applications using open source search and visualisation technologies 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 Reflections Thanks and Acknowledgements

6 Chapter 15: Utopia Documents: transforming how industrial scientists interact with the scientific literature 15.1 Utopia Documents in industry 15.2 Enabling collaboration 15.3 Sharing, while playing by the rules 15.4 History and future of Utopia Documents Chapter 16: Semantic MediaWiki in applied life science and industry: building an Enterprise Encyclopaedia 16.1 Introduction 16.2 Wiki-based Enterprise Encyclopaedia 16.3 Semantic MediaWiki 16.4 Conclusion and future directions 16.5 Acknowledgements Chapter 17: Building disease and target knowledge with Semantic MediaWiki 17.1 The Targetpedia 17.2 The Disease Knowledge Workbench (DKWB) 17.3 Conclusion 17.4 Acknowledgements Chapter 18: Chem2Bio2RDF: a semantic resource for systems chemical biology and drug discovery 18.1 The need for integrated, semantic resources in drug discovery 18.2 The Semantic Web in drug discovery 18.3 Implementation challenges 18.4 Chem2Bio2RDF architecture 18.5 Tools and methodologies that use Chem2Bio2RDF 18.6 Conclusions Chapter 19: TripleMap: a web-based semantic knowledge discovery and collaboration application for biomedical research 19.1 The challenge of Big Data 19.2 Semantic technologies

7 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 20.1 Introduction 20.2 Interoperability 20.3 Mirth 20.4 Mule ESB 20.5 Unified Medical Language System (UMLS) 20.6 Open source databases 20.7 Analytics 20.8 Final architectural overview Chapter 21: Validation and regulatory compliance of free/open source software 21.1 Introduction 21.2 The need to validate open source applications 21.3 Who should validate open source software? 21.4 Validation planning 21.5 Risk management and open source software 21.6 Key validation activities 21.7 Ongoing validation and compliance 21.8 Conclusions Chapter 22: The economics of free/open source software in industry 22.1 Introduction 22.2 Background

8 22.3 Open source innovation 22.4 Open source software in the pharmaceutical industry 22.5 Open source as a catalyst for pre-competitive collaboration in the pharmaceutical industry 22.6 The Pistoia Alliance Sequence Services Project 22.7 Conclusion Index Ordering: Order Online - Order by Fax - using the form below Order by Post - print the order form below and send to Research and Markets, Guinness Centre, Taylors Lane, Dublin 8, Ireland.

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