Knowledge-Based Bioinformatics: From analysis to interpretation (Hardcover) (知識導向的生物資訊學:從分析到詮釋)

Gil Alterovitz, Marco Ramoni

  • 出版商: Wiley
  • 出版日期: 2010-08-23
  • 定價: $2,980
  • 售價: 9.5$2,831
  • 貴賓價: 9.0$2,682
  • 語言: 英文
  • 頁數: 396
  • 裝訂: Hardcover
  • ISBN: 0470748311
  • ISBN-13: 9780470748312
  • 相關分類: 生物資訊 Bioinformatics
  • 立即出貨 (庫存=1)

買這商品的人也買了...

相關主題

商品描述

There is an increasing need throughout the biomedical sciences for a greater understanding of knowledge-based systems and their application to genomic and proteomic research. This book discusses knowledge-based and statistical approaches, along with applications in bioinformatics and systems biology. The text emphasizes the integration of different methods for analysing and interpreting biomedical data. This, in turn, can lead to breakthrough biomolecular discoveries, with applications in personalized medicine.

Key Features:

  • Explores the fundamentals and applications of knowledge-based and statistical approaches in bioinformatics and systems biology.
  • Helps readers to interpret genomic, proteomic, and metabolomic data in understanding complex biological molecules and their interactions.
  • Provides useful guidance on dealing with large datasets in knowledge bases, a common issue in bioinformatics.
  • Written by leading international experts in this field.

Students, researchers, and industry professionals with a background in biomedical sciences, mathematics, statistics, or computer science will benefit from this book. It will also be useful for readers worldwide who want to master the application of bioinformatics to real-world situations and understand biological problems that motivate algorithms.

商品描述(中文翻譯)

在生物醫學科學領域,對於知識型系統及其在基因組學和蛋白質組學研究中的應用越來越需要更深入的理解。本書討論了知識型和統計方法,以及在生物信息學和系統生物學中的應用。該文本強調了不同方法的整合,用於分析和解釋生物醫學數據。這反過來可以帶來突破性的生物分子發現,並應用於個性化醫學。

主要特點:
- 探索了生物信息學和系統生物學中知識型和統計方法的基礎和應用。
- 幫助讀者解釋基因組學、蛋白質組學和代謝組學數據,理解複雜生物分子及其相互作用。
- 提供有關在知識庫中處理大數據集的有用指導,這在生物信息學中是一個常見問題。
- 由該領域的國際領先專家撰寫。

本書將對具有生物醫學科學、數學、統計學或計算機科學背景的學生、研究人員和行業專業人士有所裨益。對於全球希望掌握生物信息學應用於實際情況並理解激發算法的生物問題的讀者也很有用。