生物信息学课程导引电子书

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内容简介

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Foreword

Chapter 1 Basics for Bioinformatics

1.1 What Is Bioinformatics

1.2 Some Basic Biology

1.3 Example Topics of Bioinformatics

References

Chapter 2 Basic Statistics for Bioinformatics

2.1 Introduction

2.2 Foundations of Statistics

2.3 Point Estimation

2.4 Hypothesis Testing

2.5 Interval Estimation

2.6 Analysis of Variance

2.7 RegressionModels

2.8 Statistical Computing Environments

References

Chapter 3 Topics in Computational Genomics

3.1 Overview: Genome Informatics

3.2 Finding Protein-Coding Genes

3.3 Identifying Promoters

3.4 Genomic Arrays and aCGH/CNP Analysis

3.5 Introduction on Computational Analysis of Transcriptional Genomics Data

3.6 Modeling Regulatory Elements

3.7 Predicting Transcription Factor Binding Sites

3.8 ModelingMotif Enrichment in Sequences

3.9 Phylogenetic Conservation of Regulatory Elements

3.10 Motif Discovery

References

Chapter 4 Statistical Methods in Bioinformatics

4.1 Introduction

4.2 Basics of Statistical Modeling and Bayesian Inference

4.3 Gene Expression andMicroarray Analysis

4.4 Sequence Alignment

4.5 Sequence Pattern Discovery

4.6 Combining Sequence and Expression Information for Analyzing Transcription Regulation

4.7 Protein Structure and Proteomics

References

Chapter 5 Algorithms in Computational Biology

5.1 Introduction

5.2 Dynamic Programming and Sequence Alignment

5.3 Greedy Algorithms for Genome Rearrangement

References

Chapter 6 Multivariate Statistical Methods in Bioinformatics Research

6.1 Introduction

6.2 Multivariate Normal Distribution

6.3 One-Sample and Two-Sample Multivariate Hypothesis Tests

6.4 Principal Component Analysis

6.5 Factor Analysis

6.6 Linear Discriminant Analysis

6.7 Classification Methods

6.8 Variable Selection

References

Chapter 7 Association Analysis for Human Diseases: Methods and Examples

7.1 Why DoWe Need Statistics?

7.2 Basic Concepts in Population and Quantitative Genetics

7.3 Genetic Linkage Analysis

7.4 Genetic Case-Control Association Analysis

7.5 Discussion

References

Chapter 8 DataMining and Knowledge Discovery Methods with Case Examples

8.1 Introduction

8.2 Different Tasks in DataMining

8.3 Some Common Tools and Techniques

8.4 Case Examples

8.5 Discussion and Conclusions

References

Chapter 9 Applied Bioinformatics Tools

9.1 Introduction

9.2 Entrez

9.3 ExPASy

9.4 Sequence Alignment

9.5 DNA Sequence Analysis

9.6 Protein Sequence Analysis

9.7 Motif Search

9.8 Phylogeny

9.9 Projects

9.10 Literature

9.11 Bioinformatics Databases

9.12 Bioinformatics Tools

9.13 Sequence Analysis

9.14 Database Search

9.15 MolecularModeling

9.16 Phylogenetic Analysis and Tree Construction

References

Chapter 10 Foundations for the Study of Structure and Function of Proteins

10.1 Introduction

10.2 Basic Concept of Protein Structure

10.3 Fundamental of Macromolecules Structures and Functions

10.4 Basis of Protein Structure and Function Prediction

Reference

Chapter 11 Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine

11.1 Introduction

11.2 Disease-Related Network

11.3 TCMZHENG-Related Network

11.4 Network-Based Study for TCM“Fu Fang”

References

Chapter 12 Advanced Topics in Bioinformatics and Computational Biology

12.1 Prokaryote Phylogeny Meets Taxonomy

12.2 Z-Curve Method and Its Applications in Analyzing Eukaryotic and Prokaryotic Genomes

12.3 Insights into the Coupling of Duplication Events and Macroevolution from an Age Profile of Transmembrane Gene Families

12.4 Evolution of Combinatorial Transcriptional Circuits in the Fungal Lineage

12.5 Can a Non-synonymous Single-Nucleotide Polymorphism (nsSNP) Affect Protein Function? Analysis from Sequence, Structure, and Enzymatic Assay

12.6 Bioinformatics Methods to Integrate Genomic and Chemical Information

12.7 From Structure-Based to System-Based Drug Design

12.8 Progress in the Study of Noncoding RNAs in Celegans

12.9 Identifying MicroRNAs and Their Targets

12.10 Topics in Computational Epigenomics

12.11 Understanding Biological Functions Through Molecular Networks

12.12 Identification of Network Motifs in Random Networks

12.13 Examples of Pattern Recognition Applications in Bioinformatics

12.14 Considerations in Bioinformatics