Systems Biology and Bioinformatics: A Computational Approach

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The availability of molecular imaging and measurement systems enables today’s biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods used in what is being coined the digital era of biology.

Written by field experts with proven track records, this authoritative textbook first provides an introduction to systems biology and its impact on biology and medicine. The book then reviews the basic principles of molecular and cell biology using a system-oriented approach, with a brief description of the high-throughput biological experiments that produce databases.

The text includes techniques to discover genes, perform nucleotide and amino acid sequence matching, and estimate static gene dynamic pathways. The book also explains how to use system-oriented models to predict the behavior of biological systems for important applications such as rational drug design.

The numerous examples and problem sets allow students to confidently explore practical systems biology applications using real examples with real biological data, making Systems Biology and Bioinformatics: A Computational Approach an ideal text for senior undergraduate and first-year graduate students.

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Product Details

  • ISBN-13: 9781420046502
  • Publisher: Taylor & Francis
  • Publication date: 4/9/2009
  • Edition description: New Edition
  • Pages: 190
  • Product dimensions: 6.40 (w) x 9.40 (h) x 0.70 (d)

Table of Contents

Cell Biology

An Introduction to Cell Structure

Proteins as Tools of the Cell

Genes: Directors of the Cell

Cell Cycle


Southern Blotting

Fluorescent In Situ Hybridization

Sanger (Dideoxy) Method

Polymerase Chain Reaction

Analyzing Protein Structure and Function

Studying Gene Expression and Function—DNA Microarrays

Review of Some Computational Methods

Introduction to Probability and Stochastic Processes Theories

Bayesian Theory

Test of Hypothesis

Expectation Maximization Method

Maximum Likelihood Theory

System Identification Theory

Computational Structural Biology: Protein Structure Prediction

Protein Structure Prediction Methods

Data Resources

Computational Structural Biology: Protein Sequence Analysis

Pairwise Sequence Matching

Multiple Sequence Alignment

Genomics and Proteomics



Methods for Identification of Differentially Expressed Genes or Proteins

Why t Test Is Not Enough?

Mixture Model Method

Genes Involved in Leukemia: A Case Study

Binary and Bayesian Networks as Static Models of Regulatory Pathways

Binary Regulator Pathways

Bayesian Networks: Algorithm

Applications and Practical Considerations

Metabolic Control Theory for Static Modeling of Metabolic Pathways

Basic Ideas

Main Concepts in Metabolic Control Theory

Mason Method

Metabolic Control Model for Galactose Regulation Pathway: A Case Study

System Identification and Control Theory for Dynamic Modeling of Biological Pathways


Modeling of Cell Cycle: A Case Study

Gene Silencing for Systems Biology

A Brief Review of RNA Interference, Small Interfering RNA, and Gene Silencing Mechanisms

Pathway Perturbation Using Gene Silencing

Simulation and Systems Biology

What Is Simulation?

Challenges to Effective Simulation

Case Studies

Software, Databases, and Other Resources for Systems Biology


Scoring Matrix

Analysis Software

Bioinformatics in MATLAB

Future Directions

Single-Cell Microarray and Systems Biology

High-Throughput Protein Assays and Systems Biology

Integration of Molecular Data with Higher-Level Datasets

Identifying Genes Controlling Macrolevel Changes

Molecular-Level Image Systems and Systems Biology


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