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Full Description
In the last decade DNA sequencing costs have decreased over a magnitude, largely because of increasing throughput by incremental advances in tools, technologies and process improvements. Further cost reductions in this and in related proteomics technologies are expected as a result of the development of new high-throughput techniques and the computational machinery needed to analyze data generated. Automation in Proteomics & Genomics: An Engineering Case-Based Approach describes the automation technology currently in the areas of analysis, design, and integration, as well as providing basic biology concepts behind proteomics and genomics. The book also discusses the current technological limitations that can be viewed as an emerging market rather than a research bottleneck. Topics covered include:
molecular biology fundamentals: from 'blueprint' (DNA) to 'task list' (RNA) to 'molecular machine' (protein); proteomics methods and technologies; modelling protein networks and interactions
analysis via automation: DNA sequencing; microarrays and other parallelization technologies; protein characterization and identification; protein interaction and gene regulatory networks
design via automation: DNA synthesis; RNA by design; building protein libraries; synthetic networks
integration: multiple modalities; computational and experimental methods; trends in automation for genomics and proteomics
new enabling technologies and future applications
Automation in Proteomics & Genomics: An Engineering Case-Based Approach is an essential guide to the current capabilities and challenges of high-throughput analysis of genes and proteins for bioinformaticians, engineers, chemists, and biologists interested in developing a cross-discipline problem-solving based approach to systems biology.
Contents
Preface. List of Contributors.
About the Editors.
SECTION 1 FUNDAMENTALS OF MOLECULAR AND CELLULAR BIOLOGY
1 The Central Dogma: From DNA to RNA, and to Protein (Takashi Ohtsuki, Masahiko Sisido).
2 Genomes to Proteomes (Ellen A. Panisko, Igor Grigoriev, Don S. Daly, Bobbie-Jo Webb-Robertson and Scott E. Baker).
SECTION 2 ANALYSIS VIA AUTOMATION.
3 High-Throughput DNA Sequencing (Tarjei S. Mikkelsen).
4 Modeling a Regulatory Network Using Temporal Gene Expression Data: Why and How (Sophie L`ebre and Gäelle Lelandais)?
5 Automated Prediction of Protein Attributes and Its Impact on Biomedicine and Drug Discovery (Kuo-Chen Chou).
6 Molecular Interaction Networks: Topological and Functional Characterizations (Xiaogang Wu and Jake Y. Chen).
SECTION 3 DESIGN VIA AUTOMATION.
7 DNA Synthesis (Jingdong Tian).
8 Computational and Experimental RNA Nanoparticle Design (Isil Severcan, Cody Geary, Luc Jaeger, Eckart Bindewald, Wojciech Kasprzak and Bruce A. Shapiro).
9 New Paradigms in Droplet-Based Microfluidics and DNA Amplification (Michael L. Samuels, John Leamon, Jonathan Rothberg, Ronald Godiska,Thomas Schoenfeld and David Mead).
10 Synthetic Networks (Jongmin Kim).
SECTION 4 INTEGRATION.
11 Molecular Modeling of CYP Proteins and its Implication for Personal Drug Design (Jing-Fang Wang, Cheng-Cheng Zhang, Jing-Yi Yan, Kuo-Chen Chou and Dong-Qing Wei).
12 Recent Progress of Bioinformatics in Membrane Protein Structural Studies (Hong-Bin Shen, Jun-Feng Wang, Li-Xiu Yao, Jie Yang and Kuo-Chen Chou).
13 Trends in Automation for Genomics and Proteomics (Gil Alterovitz, Roseann Benson, Marco Ramoni and Dmitriy Sonkin).
Index.
