| Preface | p. v |
| Acknowledgement | p. vii |
| About the Author | p. viii |
| Introduction to Modern Molecular Biology | p. 1 |
| Cells store large amounts of information in DNA | p. 1 |
| Cells process complex information | p. 7 |
| Cellular life is chemically complex and somewhat stochastic | p. 12 |
| Challenges in analyzing complex biodata | p. 19 |
| References | p. 19 |
| Biodata Explosion | p. 21 |
| Primary sequence and structure data | p. 22 |
| DNA sequence databases | p. 22 |
| Protein sequence databases | p. 27 |
| Molecular structure databases | p. 28 |
| Secondary annotation data | p. 31 |
| Motif annotations | p. 32 |
| Gene function annotations | p. 35 |
| Genomic annotations | p. 36 |
| Inter-species phylogeny and gene family annotations | p. 36 |
| Experimental and personalized data | p. 38 |
| DNA expression profiles | p. 38 |
| Proteomics data and degradomics | p. 40 |
| Protein expression profiles, 2D gel and protein interaction data | p. 41 |
| Metabolomics and metabolic pathway databases | p. 42 |
| Personalized data | p. 44 |
| Semantic and processed text data | p. 48 |
| Ontologies | p. 49 |
| Text-mined annotation data | p. 51 |
| Integrated and federated databases | p. 52 |
| References | p. 55 |
| Local Pattern Discovery and Comparing Genes and Proteins | p. 60 |
| DNA/RNA motif discovery | p. 64 |
| Single motif models: MEME, AlignAce etc. | p. 64 |
| Multiple motif models: LOGOS and MotifRegressor | p. 70 |
| Informative k-mers approach | p. 73 |
| Protein motif discovery | p. 78 |
| InterProScan and other traditional methods | p. 79 |
| Protein k-mer and other string based methods | p. 82 |
| Genetic algorithms, particle swarms and ant colonies | p. 84 |
| Genetic algorithms | p. 84 |
| Particle swarm optimization | p. 86 |
| Ant colony optimization | p. 87 |
| Sequence visualization | p. 88 |
| References | p. 90 |
| Global Pattern Discovery and Comparing Genomes | p. 97 |
| Alignment-based methods | p. 98 |
| Pairwise genome-wide search algorithms: LAGAN, AVID etc. | p. 98 |
| Multiple alignment methods: MLAGAN, MAVID, MULTIZ etc. | p. 98 |
| Dotplots | p. 103 |
| Visualization of genome comparisons | p. 104 |
| Global motif maps | p. 105 |
| Alignmentless methods | p. 108 |
| K-mer based methods | p. 109 |
| Average common substring and compressibility based methods | p. 114 |
| 2D portraits of genomes | p. 117 |
| Genome scale non-sequence data analysis | p. 125 |
| DNA physical structure based methods | p. 125 |
| Secondary structure based comparisons | p. 131 |
| References | p. 137 |
| Molecule Structure Based Searching and Comparison | p. 145 |
| Molecule structures as graphs or strings | p. 148 |
| 3D to 1D transformations | p. 148 |
| Graph matching methods | p. 151 |
| Graph visualization | p. 155 |
| Graph grammars | p. 156 |
| RNA structure comparison and prediction | p. 157 |
| Image comparison based methods | p. 162 |
| Gabor filter based methods | p. 165 |
| Image symmetry set based methods | p. 166 |
| Other graph topology based methods | p. 168 |
| References | p. 169 |
| Function Annotation and Ontology Based Searching and Classification | p. 176 |
| Annotation ontologies | p. 176 |
| Gene Ontology based mining | p. 179 |
| Sequence similarity based function prediction | p. 182 |
| Cellular location prediction | p. 184 |
| New integrative methods: Utilizing networks | p. 186 |
| Text mining bioliterature for automated annotation | p. 192 |
| Natural language processing (NLP) | p. 193 |
| Semantic profiling | p. 197 |
| Matrix factorization methods | p. 199 |
| References | p. 205 |
| New Methods for Genomics Data: SVM and Others | p. 212 |
| SVM kernels | p. 212 |
| SVM trees | p. 219 |
| Methods for microarray data | p. 221 |
| Gene selection algorithms | p. 223 |
| Gene selection by consistency methods | p. 225 |
| Genome as a time series and discrete wavelet transform | p. 227 |
| Parameterless clustering for gene expression | p. 231 |
| Transductive confidence machines, conformal predictors and ROC isometrics | p. 232 |
| Text compression methods for biodata analysis | p. 236 |
| References | p. 238 |
| Integration of Multimodal Data: Toward Systems Biology | p. 245 |
| Comparative genome annotation systems | p. 246 |
| Phylogenetics methods | p. 249 |
| Network inference from interaction and coexpression data | p. 253 |
| Bayesian inference, association rule mining and Petri nets | p. 258 |
| References | p. 262 |
| Future Challenges | p. 266 |
| Network analysis methods | p. 266 |
| Unsupervised and supervised clustering | p. 269 |
| Neural networks and evolutionary methods | p. 270 |
| Semantic web and ontologization of biology | p. 273 |
| Biological data fusion | p. 277 |
| Rise of the GPU machines | p. 279 |
| References | p. 290 |
| Index | p. 297 |
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