Bioinformatics technologies

Contents......Page 10
Preface......Page 5
1.1 Introduction......Page 15
1.2 Needs of Bioinformatics Technologies......Page 16
1.3 An Overview of Bioinformatics Technologies......Page 19
1.4 A Brief Discussion on the Chapters......Page 22
References......Page 26
2.1 Introduction......Page 28
2.2 Organization of Structural Bioinformatics......Page 30
2.3.2 Growth of Data......Page 31
2.3.3 Data Processing and Quality Control......Page 33
2.3.5 Visualization......Page 34
2.4.1 Structural Classification......Page 35
2.4.2 Structure Prediction......Page 41
2.4.3 Functional Assignments in Structural Genomics......Page 43
2.4.4 Protein-Protein Interactions......Page 45
2.4.5 Protein-Ligand Interactions......Page 47
2.5 Using Structural Bioinformatics Approaches in Drug Design......Page 50
2.6.3 The Role of Structural Bioinformatics in Systems Biology......Page 52
References......Page 53
3.1 Introduction......Page 58
3.2 Bioinformatics Data......Page 61
3.3 Transforming Data to Knowledge......Page 64
3.4 Data Warehousing......Page 67
3.5 Data Warehouse Architecture......Page 69
3.6 Data Quality......Page 71
3.7 Concluding Remarks......Page 73
References......Page 74
4.1 Introduction......Page 76
4.2 Biomedical Data Analysis......Page 77
4.2.1 Major Nucleotide Sequence Database, Protein Sequence Database, and Gene Expression Database......Page 78
4.2.2 Software Tools for Bioinformatics Research......Page 81
4.3.1 DNA Sequence......Page 84
4.3.2 DNA Data Analysis......Page 89
4.4.1 Protein and Amino Acid Sequence......Page 105
4.4.2 Protein Data Analysis......Page 112
References......Page 122
5.1 Introduction......Page 130
5.2 Artificial Neural Network......Page 133
5.3.1 Neural Network Architecture......Page 141
5.3.2 Neural Network Learning Algorithms......Page 144
5.3.3 Neural Network Applications in Bioinformatics......Page 147
5.4 Genetic Algorithm......Page 148
5.5 Fuzzy System......Page 154
References......Page 160
6.1 Introduction......Page 167
6.2 Why Systems Biotechnology?......Page 168
6.3.1 Genome Analyses......Page 170
6.3.2 Transcriptome Analyses......Page 171
6.3.3 Proteome Analyses......Page 173
6.3.4 Metabolome/Fluxome Analyses......Page 175
6.4 Integrative Approaches......Page 176
6.5 In Silico Modeling and Simulation of Cellular Processes......Page 178
6.5.1 Statistical Modeling......Page 179
6.5.2 Dynamic Modeling......Page 181
6.6 Conclusion......Page 182
References......Page 183
7.1 Introduction......Page 190
7.2 Hybrid Petri Net and Hybrid Dynamic Net......Page 194
7.3 Hybrid Functional Petri Net......Page 201
7.4.1 Definitions......Page 202
7.4.2 Relationships with Other Petri Nets......Page 208
7.5 Modeling of Biological Processes with HFPNe......Page 209
7.5.1 From DNA to mRNA in Eucaryotes – Alternative Splicing......Page 210
7.5.3 Huntington’s Disease......Page 214
7.5.4 Protein Modification – p53......Page 218
7.6 Related Works with HFPNe......Page 222
7.7 Genomic Object Net: GON......Page 223
7.7.2 GON GUI and Other Features......Page 225
7.7.3 GONML and Related Works with GONML......Page 231
7.7.4 Related Works with GON......Page 233
7.8 Visualizer......Page 235
7.8.1 Bio-processes on Visualizer......Page 237
7.8.2 Related Works with Visualizer......Page 242
7.9 BPE......Page 244
References......Page 247
8.1 Introduction......Page 254
8.2.1 Related Research......Page 256
8.2.3 PESA Sequence Assembly Algorithm......Page 260
8.3.1 Pairwise Sequence Alignment......Page 265
8.3.2 Large Smith-Waterman Pairwise Sequence Alignment......Page 267
8.4.1 Multiple Sequence Alignment......Page 268
8.4.2 Large-Scale Clustal W Multiple Sequence Alignment......Page 269
8.6 Conclusion......Page 270
References......Page 271
9.1 Introduction......Page 273
9.2.1 Hidden Markov Modeling for Sequence Identification......Page 274
9.2.2 Hidden Markov Modeling for Sequence Classification......Page 283
9.2.3 Hidden Markov Modeling for Multiple Alignment Generation......Page 288
9.2.4 Conclusion......Page 290
9.3.1 Protein Comparative Modeling......Page 291
9.3.2 Comparative Genomic Modeling......Page 294
9.4.1 Bayesian Networks......Page 297
9.4.3 Probabilistic Boolean Networks......Page 298
9.5.1 Molecular and Related Visualization Applications......Page 300
9.5.2 Molecular Mechanics......Page 304
9.5.3 Modern Computer Programs for Molecular Modeling......Page 305
References......Page 307
10.1 Introduction......Page 309
10.2 Gene Regulation......Page 311
10.2.1 Promoter Organization......Page 312
10.3 Motif Recognition......Page 313
10.4 Motif Detection Strategies......Page 315
10.4.1 Multi-genes, Single Species Approach......Page 316
10.5 Single Gene, Multi-species Approach......Page 317
10.7 Summary......Page 319
References......Page 320
11.1 Introduction......Page 323
11.2.1 What Is a Fractal?......Page 327
11.2.2 Recurrent Iterated Function System Model......Page 329
11.2.3 Moment Method to Estimate the Parameters of the IFS (RIFS) Model......Page 330
11.2.4 Multifractal Analysis......Page 331
11.3.1 One-Dimensional DNA Walk......Page 333
11.3.2 Two-Dimensional DNA Walk......Page 334
11.4.1 Chaos Game Representation of DNA Sequences......Page 335
11.4.3 Chaos Game Representation of Protein Structures......Page 336
11.4.4 Chaos Game Representation of Amino Acid Sequences Based on the Detailed HP Model......Page 337
11.5.1 Graphical Representation of Counters......Page 340
11.5.2 Fractal Dimension of the Fractal Set for a Given Tag......Page 342
11.6.1 Measure Representation of Complete Genomes......Page 345
11.6.2 Measure Representation of Linked Protein Sequences......Page 350
11.6.3 Measure Representation of Protein Sequences Based on Detailed HP Model......Page 354
References......Page 358
12.1 Introduction......Page 362
12.2 Microarray Technology for Genome Expression Study......Page 363
12.3 Image Analysis for Data Extraction......Page 365
12.3.1 Image Preprocessing......Page 366
12.3.2 Block Segmentation......Page 368
12.3.4 Spot Extraction......Page 369
12.3.5 Background Correction, Data Normalization and Filtering, and Missing Value Estimation......Page 370
12.4.1 Cluster Analysis......Page 372
12.4.2 Temporal Expression Profile Analysis and Gene Regulation......Page 380
12.4.3 Gene Regulatory Network Analysis......Page 391
References......Page 393
C......Page 398
D......Page 399
G......Page 400
L......Page 401
P......Page 402
S......Page 403
T......Page 404
Z......Page 405