Bioinformatics for biomedical science and clinical applications
著者
書誌事項
Bioinformatics for biomedical science and clinical applications
(Woodhead Publishing series in biomedicine, no. 20)
Woodhead Pub., 2013
- : hbk
大学図書館所蔵 全1件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
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  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Contemporary biomedical and clinical research is undergoing constant development thanks to the rapid advancement of various high throughput technologies at the DNA, RNA and protein levels. These technologies can generate vast amounts of raw data, making bioinformatics methodologies essential in their use for basic biomedical and clinical applications.Bioinformatics for biomedical science and clinical applications demonstrates what these cutting-edge technologies can do and examines how to design an appropriate study, including how to deal with data and address specific clinical questions. The first two chapters consider Bioinformatics and analysis of the human genome. The subsequent three chapters cover the introduction of Transcriptomics, Proteomics and Systems biomedical science. The remaining chapters move on to critical developments, clinical information and conclude with domain knowledge and adaptivity.
目次
List of figures and tables
Preface
About the author
Chapter 1: Introduction
Abstract:
1.1 Complex systems: From uncertainty to predictability
1.2 Harnessing omics technology
1.3 Bioinformatics: From theory to practice
1.4 Take home messages
Chapter 2: Genomics
Abstract:
2.1 Introduction
2.2 The human genome and variome
2.3 Genomic platforms and platform level analysis
2.4 Study designs and contrast level analysis of GWAS
2.5 Adaptive exploration of interactions of multiple genes
2.6 Somatic genomic alterations and cancer
2.7 Case studies
2.8 Take home messages
Chapter 3: Transcriptomics
Abstract:
3.1 Introduction
3.2 Transcriptomic platforms at a glance
3.3 Platform level analysis for transcriptomics
3.4 Contrast level analysis and global visualization
3.5 Module level analysis
3.6 Systems level analysis for causal inference
3.7 RNA secondary structure analysis
3.8 Case studies
3.9 Take home messages
Chapter 4: Proteomics
Abstract:
4.1 Introduction
4.2 Proteomics platforms at a glance
4.3 Protein identification by MS based proteomics
4.4 From protein sequences to structures
4.5 Protein interaction networks
4.6 Case studies
4.7 Take home messages
Chapter 5: Systems biomedical science
Abstract:
5.1 Introduction
5.2 Cell level technology and resources at a glance
5.3 Conceptual frameworks from top-down
5.4 Systems construction from bottom-up and top-down
5.5 Specific directions of systems biomedical science
5.6 Case studies
5.7 Take home messages
Chapter 6: Clinical developments
Abstract:
6.1 Fulfilling unmet medical needs
6.2 Translational medicine
6.3 Clinical product development
6.4 Critical use of clinical information
6.5 Case studies
6.6 Take home messages
Chapter 7: Conclusions
Abstract:
7.1 Change and move forward
7.2 Presentation, presentation, presentation
7.3 Domain knowledge plus adaptivity
Index
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