Bioinformatics for biomedical science and clinical applications
Author(s)
Bibliographic Information
Bioinformatics for biomedical science and clinical applications
（Woodhead Publishing series in biomedicine, no. 20）
Woodhead Pub., 2013
- : hbk
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
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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