Title
Kernel Methods in Computational Biology (Computational Molecular Biology),Used
Delivery time: 8-12 business days (International)
A detailed overview of current research in kernel methods and their application to computational biology.Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. One branch of machine learning, kernel methods, lends itself particularly well to the difficult aspects of biological data, which include high dimensionality (as in microarray measurements), representation as discrete and structured data (as in DNA or amino acid sequences), and the need to combine heterogeneous sources of information. This book provides a detailed overview of current research in kernel methods and their applications to computational biology. Following three introductory chaptersan introduction to molecular and computational biology, a short review of kernel methods that focuses on intuitive concepts rather than technical details, and a detailed survey of recent applications of kernel methods in computational biologythe book is divided into three sections that reflect three general trends in current research. The first part presents different ideas for the design of kernel functions specifically adapted to various biological data; the second part covers different approaches to learning from heterogeneous data; and the third part offers examples of successful applications of support vector machine methods.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main focus of 'Kernel Methods in Computational Biology'? A: The book provides a detailed overview of current research in kernel methods and their applications to computational biology, emphasizing their effectiveness in analyzing complex biological data.
- Q: Who is the author of this book? A: The book is authored by Bernhard Schölkopf, who is the Director of the Max Planck Institute for Intelligent Systems in Tübingen, Germany, and a Professor for Machine Learning.
- Q: What are the key topics covered in this book? A: The book covers introductory concepts in molecular and computational biology, a review of kernel methods, and various applications of these methods in computational biology.
- Q: Is this book suitable for beginners in computational biology? A: Yes, the introductory chapters are designed to help beginners understand the foundational concepts of molecular and computational biology and kernel methods.
- Q: What type of binding does this book have? A: The book is available in hardcover binding, providing durability for long-term use.
- Q: How many pages does 'Kernel Methods in Computational Biology' have? A: The book contains a total of 410 pages.
- Q: When was this book published? A: The book was published on July 16, 2004.
- Q: What condition is the used book in? A: The used book is described as being in acceptable condition.
- Q: What category does this book fall under? A: The book is categorized under Intelligence & Semantics.
- Q: Are there any specific applications of kernel methods discussed in the book? A: Yes, the book includes examples of successful applications of support vector machine methods, which are a key aspect of kernel methods in computational biology.