Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford. It provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and Applications in Genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serves as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.

List of contents

Data Mining Algorithms.- Advances in Genomic Experiment Techniques.- Case Study I: Hierarchical Clustering and Graph Algorithms for Tag-SNP Selection.- Case Study II: Constrained Unidimensional Scaling for Linkage Disequilibrium Maps.- Case Study III: Hybrid PCA-NN Algorithms for Continuous Microarray Time Series.- Discussions and Future Data Mining Projects.

Summary

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the University of Hong Kong and the Oxford University Computing Laboratory, University of Oxford. It provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. Data Mining and Applications in Genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serves as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.

Product details

• Authors: Sio-Iong Ao
• Publisher: Springer Netherlands
• Languages: English
• Product format: Hardback
• Released: 01.12.2010
• EAN: 9781402089749
• ISBN: 978-1-4020-8974-9
• No. of pages: 152
• Weight: 368 g
• Illustrations: XII, 152 p.
• Series: Lecture Notes in Electrical Engineering; Lecture Notes in Electrical En; Lecture Notes in Electrical Engineering
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > IT; B, Data Mining, computer science, molecular biology, bioinformatics, Life sciences: general issues, Data Mining and Knowledge Discovery, Human Genetics, Medical Genetics, Electronics, Microelectronics, Electronics and Microelectronics, Instrumentation, Information technology: general issues, Electronics engineering, Computational and Systems Biology, Computational Biology/Bioinformatics, Expert systems / knowledge-based systems