Read Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) by Chapman and Hall/CRC Online
Read ^ Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) PDF by # Chapman and Hall/CRC eBook or Kindle ePUB Online free. Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in
| Title | : | Biological Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) |
| Author | : | |
| Rating | : | 4.77 (706 Votes) |
| Asin | : | 1420086847 |
| Format Type | : | paperback |
| Number of Pages | : | 733 Pages |
| Publish Date | : | 2013-11-18 |
| Language | : | English |
Jake Y. Chen is an assistant professor of informatics at Indiana University, an assistant professor of computer science at Purdue University, and director of the Indiana Center for Systems Biology and Personalized Medicine. Stefano Lonardi is an associate professor of computer science and engineering at the University of California, Riverside.
Huiying Zhao said Great Book!. With the increase in the volume of data being generated in biological field, it has become necessary to perform data mining to identify interesting patterns. The selected patterns will contribute for researchers to develop tools to analyze the individual systems in detail to gain new biological insights. This book Biological Data Mining contains information obtain. "Very valuable resource!" according to Shreyas Karnik. Bioinformatics is a data rich field and data mining has become a buzzword in biology and bioinformatics, as data mining promises to find interesting patterns from the data which are useful for researchers to understand the complexity behind complex biological processes. The extracted patterns can potentially lead to enrichment of the current knowledge. This book b
The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developin
… There is a veritable alphabet soup of special software employed … there is something for everyone with an interest in bioinformatics in this book. Specialists in interdisciplinary areas will also find the book helpful. I recommend this book as a valuable resource on biological data mining. The chapters offer a wealth of useful information … Computing Reviews, January 2011… Chen and Lonardi present in this book a showcase of successful recent projects in the research area where biology, computer science, and statistics intersect. Despite the diversity of the topics presented, the editors manage to maintain homogeneity throughout the book. The book will be useful to those interested in applying data mining to biology. The editors have done a good job of pulling together the work of over 80 authors into a well-typeset product with high-resolution graph
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