190 pages | 23 B/W Illus.
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.
An Introduction to Cell Structure
Proteins as Tools of the Cell
Genes: Directors of the Cell
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
Test of Hypothesis
Expectation Maximization Method
Maximum Likelihood Theory
System Identification Theory
Computational Structural Biology: Protein Structure Prediction
Protein Structure Prediction Methods
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
Main Concepts in Metabolic Control Theory
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
Software, Databases, and Other Resources for Systems Biology
Bioinformatics in MATLAB
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