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.

Key Features

  • A coherent presentation of concepts, methodologies and practical tools that systematically lead to significant discoveries in the biomedical and clinical area
  • Real examples of cutting edge discoveries
  • The introduction of study types and technologies for all the DNA, RNA and protein levels

Readership

Researchers and postgraduates in biology, bioinformatics, medical informatics, immunology, pharmaceutical industry academic and clinical researchers in the field of bioinformatics, human biology, medicine, computational biology and computer science; Practitioners in sequencing centers, biotech, biopharmaceutical and pharmaceutical companies

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 Cl

Details

No. of pages:
170
Language:
English
Copyright:
© 2013
Published:
Imprint:
Woodhead Publishing
eBook ISBN:
9781908818232
Print ISBN:
9781907568442

About the author

K-H Liang

Kung-Hao Liang is a senior bioinformatician working at the Liver Research Center, LinKo Medical Center, Chang Gung Memorial Hospital, Taiwan. His work focuses on the power of genomics and systems biology to fulfil medical requirements and he is the author of a wide range of publications in the genomics and medical fields.

Affiliations and Expertise

LinKo Medical Center, Chang Gung Memorial Hospital, Taiwan R.O.C.