Hung Wah Johnson. / Thesis submitted in: August 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 116-121). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Problem Statement --- p.3 / Chapter 1.3 --- Outline of the thesis --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Biological Background --- p.8 / Chapter 2.2 --- Sequence Alignments --- p.9 / Chapter 2.2.1 --- Pairwise Sequences Alignment --- p.11 / Chapter 2.2.2 --- Multiple Sequences Alignment --- p.15 / Chapter 2.3 --- Neighbor Joining Tree --- p.16 / Chapter 2.4 --- Marker Extractions --- p.18 / Chapter 2.5 --- Neural Network --- p.19 / Chapter 2.6 --- Conclusion --- p.22 / Chapter 3 --- Related Work --- p.23 / Chapter 3.1 --- FASTA --- p.23 / Chapter 3.2 --- Suffix Tree --- p.25 / Chapter 4 --- Sub-Sequence Segmentation Tree --- p.28 / Chapter 4.1 --- Introduction --- p.28 / Chapter 4.2 --- Problem Statement --- p.29 / Chapter 4.3 --- Design --- p.33 / Chapter 4.4 --- Time and space complexity analysis --- p.38 / Chapter 4.4.1 --- Performance Evaluation --- p.40 / Chapter 4.5 --- Summary --- p.48 / Chapter 5 --- Applications: Global Sequences Alignment --- p.51 / Chapter 5.1 --- Introduction --- p.51 / Chapter 5.2 --- Problem Statement --- p.53 / Chapter 5.3 --- Pairwise Alignment --- p.53 / Chapter 5.3.1 --- Algorithm --- p.53 / Chapter 5.3.2 --- Time and Space Complexity Analysis --- p.64 / Chapter 5.4 --- Multiple Sequences Alignment --- p.67 / Chapter 5.4.1 --- The Clustalw Algorithm --- p.68 / Chapter 5.4.2 --- MSA Using SSST --- p.70 / Chapter 5.4.3 --- Time and Space Complexity Analysis --- p.70 / Chapter 5.5 --- Experiments --- p.71 / Chapter 5.5.1 --- Experiment Setting --- p.72 / Chapter 5.5.2 --- Experimental Results --- p.72 / Chapter 5.6 --- Summary --- p.80 / Chapter 6 --- Applications: Marker Extractions --- p.81 / Chapter 6.1 --- Introduction --- p.81 / Chapter 6.2 --- Problem Statement --- p.82 / Chapter 6.3 --- The Multiple Sequence Alignment Approach --- p.85 / Chapter 6.3.1 --- Design --- p.85 / Chapter 6.4 --- Reference Sequence Alignment Approach --- p.88 / Chapter 6.4.1 --- Design --- p.90 / Chapter 6.5 --- Time and Space Complexity Analysis --- p.95 / Chapter 6.6 --- Experiments --- p.95 / Chapter 6.7 --- Summary --- p.99 / Chapter 7 --- HBV Application Framework --- p.101 / Chapter 7.1 --- Motivations --- p.101 / Chapter 7.2 --- The Procedure Flow of the Application --- p.102 / Chapter 7.2.1 --- Markers Extractions --- p.103 / Chapter 7.2.2 --- Rules Training and Prediction --- p.103 / Chapter 7.3 --- Results --- p.105 / Chapter 7.3.1 --- Clustering --- p.106 / Chapter 7.3.2 --- Classification --- p.107 / Chapter 7.4 --- Summary --- p.110 / Chapter 8 --- Conclusions --- p.112 / Chapter 8.1 --- Contributions --- p.112 / Chapter 8.2 --- Future Works --- p.114 / Chapter 8.2.1 --- HMM Learning --- p.114 / Chapter 8.2.2 --- Splice Sites Learning --- p.114 / Chapter 8.2.3 --- Faster Algorithm for Multiple Sequences Alignment --- p.115 / Bibliography --- p.121