The First Book to Describe the Technical and Practical Elements of Chemical Text Mining
Explores the development of chemical structure extraction capabilities and how to incorporate these technologies in daily research work
For scientific researchers, finding too much information on a subject, not finding enough information, or not being able to access full text documents often costs them time, money, and quality. Addressing these concerns, Chemical Information Mining: Facilitating Literature-Based Discovery presents strategic ideas for properly selecting and successfully using the best text mining tools for scientific research.
Links chemical and biological entities at the heart of life science research
The book focuses on information extraction issues, highlights available solutions, and underscores the value of these solutions to academic and commercial scientists. After introducing the drivers behind chemical text mining, it discusses chemical semantics. The contributors describe the tools that identify and convert chemical names and images to structure-searchable information. They also explain natural language processing, name entity recognition concepts, and semantic web technologies. Following a section on current trends in the field, the book looks at where information mining approaches fit into the research needs within the life sciences.
Shaping the future of scientific information and knowledge management
By building knowledge and competency in the growing area of literature-based discovery, this book shows how text mining of the chemical literature can increase drug discovery opportunities and enhance life science research.
Preface. Illustrating the Power of Information in Life Science Research. Chemical Information Mining: A New Paradigm. Automated Identification and Conversion of Chemical Names to Structure-Searchable Information. Identification of Chemical Images and Conversion to Structure-Searchable Information. Chemical Entity Formatting. Chemical XML Formatting. Linking Chemical and Biological Information with Natural Language Processing. Semantic Web. The Future of Searching for Chemical Information. Summary and Closing Statements. Index.