Biological Data Mining
暫譯: 生物數據挖掘

Chen, Jake Y., Lonardi, Stefano

  • 出版商: CRC
  • 出版日期: 2017-06-07
  • 售價: $3,630
  • 貴賓價: 9.5$3,449
  • 語言: 英文
  • 頁數: 733
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1138116580
  • ISBN-13: 9781138116580
  • 相關分類: Data-mining
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics.

The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. 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. The last part explores emerging data mining opportunities for biomedical applications.

This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. 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.

商品描述(中文翻譯)

像是一個消耗大量數據的渦輪引擎,先進的數據挖掘在過去二十年中一直推動著後基因組生物學研究。反映這一增長的《生物數據挖掘》呈現了當前生物和醫學研究中的全面數據挖掘概念、理論和應用。每一章均由一支傑出的跨學科數據挖掘研究團隊撰寫,涵蓋了最前沿的生物學主題。

本書的第一部分討論了分析和挖掘生物序列及結構所面臨的挑戰和機遇,以獲得對分子功能的深入了解。第二部分則針對解釋高通量Omics數據所出現的計算挑戰進行探討。接著,本書描述了數據挖掘與計算相關領域之間的關係,包括知識表示、信息檢索以及結構化和非結構化生物數據的數據整合。最後一部分探討了生物醫學應用中出現的數據挖掘機會。

本卷檢視了在快速增長的基因組生物學領域中開發和應用新數據挖掘技術的概念、問題、進展和趨勢。通過學習所呈現的概念和案例研究,讀者將獲得重要的見解,並為未來類似的生物數據挖掘項目開發實用的解決方案。

作者簡介

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.

作者簡介(中文翻譯)

Jake Y. Chen 是印第安納大學的資訊學助理教授、普渡大學的計算機科學助理教授,以及印第安納系統生物學與個人化醫學中心的主任。

Stefano Lonardi 是加州大學河濱分校的計算機科學與工程副教授。