Structural Bioinformatics: An Algorithmic Approach, 1st Edition (Hardback) book cover

Structural Bioinformatics

An Algorithmic Approach, 1st Edition

By Forbes J. Burkowski

Chapman and Hall/CRC

429 pages | 24 Color Illus. | 124 B/W Illus.

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pub: 2008-10-30
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The Beauty of Protein Structures and the Mathematics behind Structural Bioinformatics

Providing the framework for a one-semester undergraduate course, Structural Bioinformatics: An Algorithmic Approach shows how to apply key algorithms to solve problems related to macromolecular structure.

Helps Students Go Further in Their Study of Structural Biology

Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in a 3D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design.

At the Crossroads of Biology, Mathematics, and Computer Science

Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).


… the book presents a number of topics in structural bioinformatics, aiming to emphasize the beauty of the area as well as some of the main problems. It targets advanced undergraduate students and hence the description of more complicated algorithms is avoided. It nevertheless provides an interesting introduction to the area.

—Lucian Ilie, Mathematical Reviews, Issue 2009k

Table of Contents


The Study of Structural Bioinformatics


Small Beginnings

Structural Bioinformatics and the Scientific Method

A More Detailed Problem Analysis: Force Fields

Modeling Issues

Sources of Error


Introduction to Macromolecular Structure


Overview of Protein Structure

Overview of RNA Structure

Data Sources, Formats, and Applications


Sources of Structural Data

PDB File Format

Visualization of Molecular Data

Software for Structural Bioinformatics

Dynamic Programming



A DP Example: The Al Gore Rhythm for Giving Talks

A Recipe for Dynamic Programming

Longest Common Subsequence

RNA Secondary Structure Prediction


Introduction to the Problem

The Nussinov Dynamic Programming

The MFOLD Algorithm: Terminology

Protein Sequence Alignment

Protein Homology

Variations in the Global Alignment Algorithm

The Significance of a Global Alignment

Local Alignment

Protein Geometry


Calculations Related to Protein Geometry

Ramachandran Plots

Inertial Axes

Coordinate Transformations



Translation Transformations

Rotation Transformations

Isometric Transformations

Structure Comparison, Alignment, and Superposition



Techniques for Structural Comparison

Scoring Similarities and Optimizing Scores

Superposition Algorithms

Algorithms Comparing Relationships within a Protein

Machine Learning


Issues of Complexity

Prediction via Machine Learning

Data Used during Training and Testing

Objectives of the Learning Algorithm

Linear Regression

Ridge Regression

Preamble for Kernel Methods

Kernel Functions


Heuristics for Classification

Nearest Neighbor Classification

Support Vector Machines

Linearly Nonseparable Data

Support Vector Machines and Kernels

Expected Test Error


Overview of the Appendices


About the Series

Chapman & Hall/CRC Mathematical and Computational Biology

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Subject Categories

BISAC Subject Codes/Headings:
COMPUTERS / Programming / Games
SCIENCE / Life Sciences / Biology / General
SCIENCE / Biotechnology
SCIENCE / Physics