Computational biology and bioinformatics : gene regulation : gene, RNA, protein, epigenetics / editor, Ka-Chun Wong. -- Boca Raton : Taylor & Francis, 2016. – (58.17115/C738b)

Contents

Preface  v

List of Reviewers  vii

Section 1: Genes

1.  A Survey of the Computational Methods for Enhancers and Enhancer-target Predictions  3

1. Introduction    3

2. Computational methods for enhancer prediction  7

3. Computational methods for enhancer target prediction  15

4. Databases useful for enhancer and enhancer-promoter association prediction  20

5. Conclusions and discussions  21

2. Cormotif: An R Package for Jointly Detecting Differential Gene Expression in Multiple Studies  28

1. Introduction  29

2. Methods  32

3. Simulations  35

4. Discussion  41

5. Software  43

3. Granger Causality for Time Series Gene Expression Data  48

1. Introduction  49

2. Granger Causality for Sets of Time Series  50

3. Canonical Correlation Analysis and Granger Causality  51

4. Functional Clustering in Terms of Granger Causality  58

5. Network Construction from Large Datasets  63

6. Software  64

Appendix  64

Acknowledgments  65

Section 2: RNAs

4. RNA Sequencing and Gene Expression Regulation  71

1. The Fundamentals of DNA, RNA and Gene  72

2. The Fundamentals of Gene Expression and Regulation  84

5. Modern Technologies and Approaches for Decoding Non-Coding Rna-Mediated Biological Networks in Systems Biology and Their Applications  106

1. Introduction  106

2. ncRNA-mediated regulatory networks generation and visualization  109

3. Interactomics  111

4. Network visualization tools  116

5. Biological Network Architecture  117

6. Analyzing ncRNA-mediated regulatory network  120

7. Application of non-coding RNA-mediated biological network  123

8. Challenges and Future Directions  124

Section 3: Proteins

6. Annotation of Hypothetical Proteins- a Functional Genomics Approach  135

1. Introduction  136

2. Methodology for functional annotation of hypothetical proteins  142

3. Conclusion  153

7. Protein-Protein Functional Linkage Predictions: Bringing Regulation to Context  159

1. Protein Functions in the Post-Genomic Era  160

2. Computational Methods for Predicting Functional Linkages between Proteins  161

3. Phylogenetic Profiling  162

4. Analysis of Correlated Mutations in Protein Families by Mirrortree Approach: Indicator of Protein-Protein Interaction  165

5. Chromosomal Proximity of Genes Reflects their Functional Links  166

6. Expression Similarity of Genes as an Indicator of Functional Linkage. 169

7. From Transcriptional Regulation to Predicting Protein-Protein Functional Linkages: A Novel Approach  170

8. Measuring Prediction Performance of Methods  171

9. Perspectives  173

Acknowledgements  174

Section 4: Epigenetics

8. Epigenomic Analysis of Chromatin Organization and DNA Methylation.  181

1. Introduction  181

2. Chromatin organization  182

4. Bioinformatics databases and resources  197

5. Applications of epigenomics  199

6. Emerging fields in epigenetics  201

Acknowledgements  203

9. Gene Body Methylation and Transcriptional Regulation: Statistical Modelling and More  212

1. Introduction  212

2. Methylation Data and global patterns  215

3. Global correlation and patterns between gene methylation and expression  217

4. Statistical modeling and data mining  219

5. Gene body methylation and splicing  222

6. Discussion  223

7. Methods  224

8. Acknowledgements  227

Section 5: Case Study

10. Computational Characterization of Non-small-cell Lung Cancer with EGFR Gene Mutations and its Applications to Drug Resistance Prediction    233

1. Introduction  234

2. Computational Modeling &Interaction between an EGFR Tyrosine Kinase and an Inhibitor  238

3. Characterization of EGFR or ErbB-3 Heterodimerization Using Computer Simulations  246

4. New-generation Irreversible EGFR TKIs  250

Acknowledgements  252

Section 6: Advanced Topics

11. Quality Assurance in Genome-Scale Bioinformatics Analyses  259

1. Introduction    259

2. Whole genome sequencing analysis for genomic medicine  260

3. The problem &quality assurance  264

4. Standard validation and QC approaches used in diagnostic laboratories  264

5. Introduction to a software-testing framework  267

6. Software testing approaches, applications and evaluations  268

7. Cloud-based testing as a service (TaaS) for bioinformatics  273

8. Future Directions  275

Acknowledgements  275

12. Recent Computational Trends in Biological Sequence Alignment  279

1. Introduction  279

2. Pairwise Sequence Alignment  280

3. Acceleration of Sequence Alignment Algorithms:  291

4. Gene Tracer Application  296

Acknowledgement  302

13. State Estimation and Process Monitoring of Nonlinear Biological Phenomena Modeled by S-systems  305

1. Introduction  305

2. State Estimation in Non-linear Biological Systems  308

3. Description of State Estimation Techniques  309

4. Faults Detection of Biological Systems Representing Continousily Stirred Tank Reactor Model  313

5. Simulation Results Analysis  318

6. Conclusions  326

Acknowledgment  327

14. Next-Generation Sequencing and Metagenomics  331

1. Introduction  331

Acknowledgements  346

15. Metabolic Engineering: Dimensions and Applications  352

1. Introduction  352

2. Metabolic flux balance analysis  354

3. Metabolic engineering in microorganisms  356

4. Metabolic engineering in plants  360

5. Transcription factors vs. enzymes  363

6. Metabolic trafficking and sequestration  364

7. Genome editing  364

8. Metabolic engineering in human disorders  365

9. Principles and techniques of metabolic engineering in human diseases 366

10. Heart Models  366

11. Computational Biology has come to aid metabolic engineering  369

13. Computational Biology in identify metabolic pathways  374

14. Bioinformatics in identifying genome editing elements such as CRISPRs  375

15. Concluding remarks  376

16. Methods to Identify Evolutionary Conserved Regulatory Elements Using Molecular Phylogenetics in Microbes  381

1. Functional annotation of regulatory proteins  381

2. Structure of phylogenetic tree  382

3. Methods of phylogenetics inference  383

4. Computational methods to identify conserved regulatory elements in microbes  384

5. Phylogenetic-based methods to identify regulatory proteins  386

6. Tools and web-servers for phylogenetic analysis  389

7. Protocol for phylogenetics analysis with Phylogeny.fr  394

8. Protocol of phylogenetics analysis using PhyMLL  398

9. Protocol of phylogenetics analysis using BioNJ  400

Acknowledgements  401

17. Improved Protein Model Ranking through Topological Assessment  406

1. Introduction  407

2. Methodology  412

3. Results  2  416

4. Discussion  418

5. Conclusion  2  422

6. Limitations and Further Research Possibilities  422

Acknowledgements  423

Index  425