Sung Algorithms in Bioinformatics

A Practical Introduction
1. Auflage 2011
ISBN: 978-1-4200-7034-7
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 407 Seiten

Reihe: Chapman & Hall/CRC Mathematical & Computational Biology

Thoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions

Developed from the author’s own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation and precisely defines the corresponding computational problems. He also includes detailed examples to illustrate each algorithm and end-of-chapter exercises for students to familiarize themselves with the topics. Supplementary material is available at http://www.comp.nus.edu.sg/~ksung/algo_in_bioinfo/

This classroom-tested textbook begins with basic molecular biology concepts. It then describes ways to measure sequence similarity, presents simple applications of the suffix tree, and discusses the problem of searching sequence databases. After introducing methods for aligning multiple biological sequences and genomes, the text explores applications of the phylogenetic tree, methods for comparing phylogenetic trees, the problem of genome rearrangement, and the problem of motif finding. It also covers methods for predicting the secondary structure of RNA and for reconstructing the peptide sequence using mass spectrometry. The final chapter examines the computational problem related to population genetics.

Zielgruppe

Advanced undergraduate and beginning graduate students in bioinformatics or computational biology; mathematicians, computer scientists, statisticians, and biologists in computational biology or bioinformatics.

Autoren/Hrsg.

Sung, Wing-Kin

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
• Naturwissenschaften Biowissenschaften Biowissenschaften

Inhaltsverzeichnis

Introduction to Molecular Biology
DNA, RNA, Protein

Genome, Chromosome, and Gene

Replication and Mutation of DNA

Central Dogma (From DNA to Protein)

Post-Translation Modification (PTM)

Population Genetics

Basic Biotechnological Tools

Brief History of Bioinformatics
Sequence Similarity
Introduction
Global Alignment Problem
Local Alignment

Semi-Global Alignment
Gap Penalty

Scoring Function
Suffix Tree
Introduction

Suffix Tree

Simple Applications of Suffix Tree
Construction of Suffix Tree
Suffix Array
FM-Index
Approximate Searching Problem
Database Search

Introduction

Smith–Waterman Algorithm

FastA

BLAST
Variations of the BLAST Algorithm

Q-Gram Alignment Based on Suffix ARrays (QUASAR)

Locality-Sensitive Hashing

BWT-SW

Are Existing Database Searching Methods Sensitive Enough?
Multiple Sequence Alignment

Introduction

Formal Definition of Multiple Sequence Alignment Problem

Dynamic Programming Method
Center Star Method

Progressive Alignment Method

Iterative Method

Genome Alignment

Introduction

Maximum Unique Match (MUM)

Mutation Sensitive Alignment
Dot Plot for Visualizing the Alignment

Phylogeny Reconstruction
Introduction
Character-Based Phylogeny Reconstruction Algorithm

Distance-Based Phylogeny Reconstruction Algorithm

Bootstrapping

Can Tree Reconstruction Methods Infer the Correct Tree?
Phylogeny Comparison

Introduction

Similarity Measurement
Dissimilarity Measurements
Consensus Tree Problem
Genome Rearrangement

Introduction

Types of Genome Rearrangements

Computational Problems

Sorting Unsigned Permutation by Reversals

Sorting Signed Permutation by Reversals

Motif Finding

Introduction

Identifying Binding Regions of TFs

Motif Model

The Motif Finding Problem

Scanning for Known Motifs

Statistical Approaches
Combinatorial Approaches

Scoring Function
Motif Ensemble Methods
Can Motif Finders Discover the Correct Motifs?
Motif Finding Utilizing Additional Information
RNA Secondary Structure Prediction

Introduction

Obtaining RNA Secondary Structure Experimentally

RNA Structure Prediction Based on Sequence Only

Structure Prediction with the Assumption That There Is No Pseudoknot
Nussinov Folding Algorithm

ZUKER Algorithm

Structure Prediction with Pseudoknots
Peptide Sequencing

Introduction

Obtaining the Mass Spectrum of a Peptide

Modeling the Mass Spectrum of a Fragmented Peptide

De novo Peptide Sequencing Using Dynamic Programming

De novo Sequencing Using Graph-Based Approach

Peptide Sequencing via Database Search

Population Genetics

Introduction
Hardy–Weinberg Equilibrium

Linkage Disequilibrium
Genotype Phasing
Tag SNP Selection
Association Study
References
Index
Exercises appear at the end of each chapter.

Über Autor(innen)

Wing-Kin Sung is an associate professor at the National University of Singapore.