About this book
Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more.
Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place.
Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering.
Forward by Professor Jiawei Han, University of Illinois at Urbana-Champaign.
- DOI https://doi.org/10.1007/978-0-387-69937-0
- Copyright Information Springer Science+Business Media, LLC 2007
- Publisher Name Springer, Boston, MA
- eBook Packages Computer Science Computer Science (R0)
- Print ISBN 978-0-387-69936-3
- Online ISBN 978-0-387-69937-0
- Series Print ISSN 1386-2944
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