Big Data Analytics in Genomics

  • 出版商: Springer
  • 出版日期: 2016-11-01
  • 售價: $7,610
  • 貴賓價: 9.5$7,230
  • 語言: 英文
  • 頁數: 428
  • 裝訂: Hardcover
  • ISBN: 3319412787
  • ISBN-13: 9783319412788
  • 相關分類: 大數據 Big-dataData Science
  • 海外代購書籍(需單獨結帳)

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商品描述

This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace.  To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA.  In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science.  Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.


商品描述(中文翻譯)

這本專書探討了大數據分析和基因組學之間新興的交叉領域。近年來,高通量测序技術使得基因組學的大規模數據生成成為可能,導致了一些國際項目的進行,以前所未有的速度累積了大量的基因組數據。為了在合理的時間範圍內從這些數據中揭示新的基因組洞察,傳統的數據分析方法可能不足或不可擴展,因此需要開發適用於基因組學的大數據分析方法。本書介紹的計算方法旨在使用大數據解決重要的生物學問題,適用於該領域的新手或老手。

本書提供了十三篇經同行評審的論文,由來自不同地區的國際領先專家撰寫,包括阿根廷、巴西、中國、法國、德國、香港、印度、日本、西班牙和美國。具體而言,本書涵蓋了三個主要領域:統計分析、計算分析和癌症基因組分析。其中涉及的主題包括:基因組數據整合分析的統計方法、蛋白質功能預測的計算方法,以及大數據挖掘癌症中的機器學習技術的觀點。本書獨立完整,適合研究生閱讀,同時也適用於生物信息學家、計算生物學家以及從基因組學、大數據、分子遺傳學、數據挖掘、生物統計學、生物醫學科學、癌症研究、醫學研究和生物學到機器學習和計算機科學等領域的研究人員。讀者將會發現本書對於理解大數據在基因組學中的作用至關重要,這使得本書成為進一步研究該主題的寶貴資源。