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Bioinformatics in the Post-Genomic Era: Genome, Transcriptome, Proteome, and Information-Based Medicine

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Bioinformatics in the Post-Genomic Era: Genome, Transcriptome, Proteome, and Information-Based Medicine


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  • Copyright 2005
  • Dimensions: 7x9-1/4
  • Pages: 408
  • Edition: 1st
  • Book
  • ISBN-10: 0-321-17386-4
  • ISBN-13: 978-0-321-17386-7

"Augen's book provides a thorough review of bioinformatics that presages the coming era of information-based medicine."
—John Reynders, VP of Informatics, Celera Genomics

"Augen is to be congratulated on producing an indispensable book. He not only lays out and explains the essential tools in bioinformatics, but he also validates the critical role that computational biology will play in the future of medical research. This is a fabulous achievement—there is something here for novice and expert alike."
—Kevin Davies, Editor-in-Chief, Bio-IT World

"Jeff has created an erudite, yet amazingly accessible overview of the intersection between biology, biomedicine, and high-performance computing."
—Andrea Califano, Director, Genome Center Bioinformatics, Columbia University

"This book is essential for anyone wishing to understand the information technology transformation of the life sciences."
—W.R. Pulleyblank, Director, Deep Computing Institute, IBM Research

"Because of its unusually broad scope, Jeff Augen's new book has the capacity to deliver value to a wide variety of audiences. As a longtime investor in biotechnology and healthcare, I find the discussions surrounding the future of medicine and information technology particularly interesting and useful."
—G. Steven Burrill, Chief Executive Officer, Burrill and Company

"Augen takes you on a complete guided tour of computational biology, combining historical perspectives with discussions of the leading-edge technologies being employed today. This book would be useful for anyone in the field. It provides an entire overview to scientists new to computational biology, while giving experts detailed information about new developments in the field."
—Salvatore Salamone, Senior IT Editor, Bio-IT World and Health-IT World

"There are books about bioinformatics with a focus on information technology and books on molecular biology with a focus on bioscience, but I am not aware of any book that provides a summary of fundamentals of both bioscience and information science with a technical bridge between the two disciplines. This book is unique in covering theoretical and practical aspects of bioinformatics. Everyone from biologists and geneticists to computer scientists and engineers will benefit from Augen's book."
—O.K. Baek, Chief Architect, Biomedical Informatics and Information-Based Medicine, IBM

Today, advances in high-performance computing, data management, and the Internet are transforming many aspects of biomedical research and have produced a new generation of tools for studying gene and protein sequences, macromolecular structures, and metabolic systems. These tools have greatly accelerated the drug discovery and testing process and promise to change the way diseases are predicted and treated in the future.

Bioinformatics in the Post-Genomic Era is the first comprehensive look at the role of information technology in biological and medical research. Bridging these two disciplines, the book's structure parallels the flow of biological information from gene to message, protein, and metabolic system. Along the way, industry expert Jeff Augen covers both theoretical and practical aspects of bioinformatics, giving readers a vision of the future of medical research while providing technical details working professionals can use today.

  • Inside, you will find in-depth information on the following:
  • Gene and protein sequence databases
  • Bioinformatic tools
  • Transcription profiling
  • The proteome and the protein translation process
  • Protein structure prediction
  • Medical informatics and information-based medicine
  • Little-discussed topics such as transcription profiling of minor messages and pattern-discovery algorithms and neural networks
  • Cutting-edge developments such as high-throughput whole-genome sequencing, systems biology, and presymptomatic disease prediction.

Designed for both biomedical researchers and students, this book will become an indispensable aid to anyone seeking to understand the links between information technology, molecular biology, and clinical medicine.

© Copyright Pearson Education. All rights reserved.

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Table of Contents


1. Introduction.


Computationally Intense Problems: A Central Theme in Modern Biology.

Building the Public Infrastructure.

The Human Genome’s Several Layers of Complexity.

Toward Personalized Medicine.

Illnesses are Polygenic.

New Science, New Infrastructure.

The Proactive Future of Information-Based Medicine.

2. Introduction to Bioinformatics.


The Emergence of Bioinformatics.

The Public Database Infrastructure.

Building Database Infrastructure for Bioinformatics.

Traditional Bioinformatic Tools and Algorithms.


3. Gene Structure.


The Central Dogma of Molecular Biology.

The Genetic Code.

Structure and Content of the Genome.

Computational Techniques for the Identification of Genomic Features.

High-Throughput Gene Sequencing.


4. Computational Techniques for Sequence Analysis.


Hidden Markov Models.

Perceptrons and Neural Networks.

Pattern Discovery, Single Nucleotide Polymorphisms, and Haplotype Identification.


5. Transcription.


The Transcriptome.

Technologies for Transcriptional Profiling.

Hierarchical Clustering.


6. Overview of the Proteome and the Protein Translation Process.


Ribosomal Structure and the Protein Translation Process.

Special Features of the Eukaryotic-Translation Process.


7. Protein Structure Prediction.


Overview of Ab Initio and Database-Driven Approaches.

Overview of   Protein Structure.

Protein Structure Databases.

Ab Initio Structure Prediction.

Predicting Lead–Target Interactions.


8. Medical Informatics and Information-Based Medicine.


The Continuous Evolution in Understanding that Leads to Genomic Medicine.

Electronic Medical Records.

Grid Computing and Medical Informatics.

Modeling and Predicting Disease.


9. New Themes in Bioinformatics.


Overview of Parallel Computing and Workflow Distribution in Bioinformatics.

Workflow Computing.

High-Performance Computing and Systems Biology.

The Delineation of Metabolic Pathways.

Systems Biology.


Further Reading.



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