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  • Pattern Recognition in Computational Molecular Biology: Techniques and

    • Item No : 167537067713
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    • LIST OF CONTRIBUTORS xxi PREFACE xxvii I PATTERN RECOGNITION IN SEQUENCES 1 1 COMBINATORIAL HAPLOTYPING PROBLEMS 3 Giuseppe Lancia 1.1 Introduction / 3 1.2 Single Individual Haplotyping / 5 1.3 Population Haplotyping / 12 References / 23 2 ALGORITHMIC PERSPECTIVES OF THE STRING BARCODING PROBLEMS 28 Sima Behpour and Bhaskar DasGupta 2.1 Introduction / 28 2.2 Summary of Algorithmic Complexity Results for Barcoding Problems / 32 2.3 Entropy-Based Information Content Technique for Designing Approximation Algorithms for String Barcoding Problems / 34 2.4 Techniques for Proving Inapproximability Results for String Barcoding Problems / 36 2.5 Heuristic Algorithms for String Barcoding Problems / 39 2.6 Conclusion / 40 Acknowledgments / 41 References / 41 3 ALIGNMENT-FREE MEASURES FOR WHOLE-GENOME COMPARISON 43 Matteo Comin and Davide Verzotto 3.1 Introduction / 43 3.2 Whole-Genome Sequence Analysis / 44 3.3 Underlying Approach / 47 3.4 Experimental Results / 54 3.5 Conclusion / 61 Author's Contributions / 62 Acknowledgments / 62 References / 62 4 A MAXIMUM LIKELIHOOD FRAMEWORK FOR MULTIPLE SEQUENCE LOCAL ALIGNMENT 65 Chengpeng Bi 4.1 Introduction / 65 4.2 Multiple Sequence Local Alignment / 67 4.3 Motif Finding Algorithms / 70 4.4 Time Complexity / 75 4.5 Case Studies / 75 4.6 Conclusion / 80 References / 81 5 GLOBAL SEQUENCE ALIGNMENT WITH A BOUNDED NUMBER OF GAPS 83 Carl Barton, Tomás Flouri, Costas S. Iliopoulos, and Solon P. Pissis 5.1 Introduction / 83 5.2 Definitions and Notation / 85 5.3 Problem Definition / 87 5.4 Algorithms / 88 5.5 Conclusion / 94 References / 95 II PATTERN RECOGNITION IN SECONDARY STRUCTURES 97 6 A SHORT REVIEW ON PROTEIN SECONDARY STRUCTURE PREDICTION METHODS 99 Renxiang Yan, Jiangning Song, Weiwen Cai, and Ziding Zhang 6.1 Introduction / 99 6.2 Representative Protein Secondary Structure Prediction Methods / 102 6.3 Evaluation of Protein Secondary Structure Prediction Methods / 106 6.4 Conclusion / 110 Acknowledgments / 110 References / 111 7 A GENERIC APPROACH TO BIOLOGICAL SEQUENCE SEGMENTATION PROBLEMS: APPLICATION TO PROTEIN SECONDARY STRUCTURE PREDICTION 114 Yann Guermeur and Fabien Lauer 7.1 Introduction / 114 7.2 Biological Sequence Segmentation / 115 7.3 MSVMpred / 117 7.4 Postprocessing with A Generative Model / 119 7.5 Dedication to Protein Secondary Structure Prediction / 120 7.6 Conclusions and Ongoing Research / 125 Acknowledgments / 126 References / 126 8 STRUCTURAL MOTIF IDENTIFICATION AND RETRIEVAL: A GEOMETRICAL APPROACH 129 Virginio Cantoni, Marco Ferretti, Mirto Musci, and Nahumi Nugrahaningsih 8.1 Introduction / 129 8.2 A Few Basic Concepts / 130 8.3 State of the Art / 135 8.4 A Novel Geometrical Approach to Motif Retrieval / 138 8.5 Implementation Notes / 149 8.6 Conclusions and Future Work / 151 Acknowledgment / 152 References / 152 9 GENOME-WIDE SEARCH FOR PSEUDOKNOTTED NONCODING RNAs: A COMPARATIVE STUDY 155 Meghana Vasavada, Kevin Byron, Yang Song, and Jason T.L. Wang 9.1 Introduction / 155 9.2 Background / 156 9.3 Methodology / 157 9.4 Results and Interpretation / 161 9.5 Conclusion / 162 References / 163 III PATTERN RECOGNITION IN TERTIARY STRUCTURES 165 10 MOTIF DISCOVERY IN PROTEIN 3D-STRUCTURES USING GRAPH MINING TECHNIQUES 167 Wajdi Dhifli and Engelbert Mephu Nguifo 10.1 Introduction / 167 10.2 From Protein 3D-Structures to Protein Graphs / 169 10.3 Graph Mining / 172 10.4 Subgraph Mining / 173 10.5 Frequent Subgraph Discovery / 173 10.6 Feature Selection / 179 10.7 Feature Selection for Subgraphs / 180 10.8 Discussion / 183 10.9 Conclusion / 185 Acknowledgments / 185 References / 186 11 FUZZY AND UNCERTAIN LEARNING TECHNIQUES FOR THE ANALYSIS AND PREDICTION OF PROTEIN TERTIARY STRUCTURES 190 Chinua Umoja, Xiaxia Yu, and Robert Harrison 11.1 Introduction / 190 11.2 Genetic Algorithms / 192 11.3 Supervised Machine Learning Algorithm / 201 11.4 Fuzzy Application / 204 11.5 Conclusion / 207 References / 208 12 PROTEIN INTER-DOMAIN LINKER PREDICTION 212 Maad Shatnawi, Paul D. Yoo, and Sami Muhaidat 12.1 Introduction / 212 12.2 Protein Structure Overview / 213 12.3 Technical Challenges and Open Issues / 214 12.4 Prediction Assessment / 215 12.5 Current Approaches / 216 12.6 Domain Boundary Prediction Using Enhanced General Regression Network / 220 12.7 Inter-Domain Linkers Prediction Using Compositional Index and Simulated Annealing / 227 12.8 Conclusion / 232 References / 233 13 PREDICTION OF PROLINE CIS-TRANS ISOMERIZATION 236 Paul D. Yoo, Maad Shatnawi, Sami Muhaidat, Kamal Taha, and Albert Y. Zomaya 13.1 Introduction / 236 13.2 Methods / 238 13.3 Model Evaluation and Analysis / 243 13.4 Conclusion / 245 References / 245 IV PATTERN RECOGNITION IN QUATERNARY STRUCTURES 249 14 PREDICTION OF PROTEIN QUATERNARY STRUCTURES 251 Akbar Vaseghi, Maryam Faridounnia, Soheila Shokrollahzade, Samad Jahandideh, and Kuo-Chen Chou 14.1 Introduction / 251 14.2 Protein Structure Prediction / 255 14.3 Template-Based Predictions / 257 14.4 Critical Assessment of Protein Structure Prediction / 258 14.5 Quaternary Structure Prediction / 258 14.6 Conclusion / 261 Acknowledgments / 261 References / 261 15 COMPARISON OF PROTEIN QUATERNARY STRUCTURES BY GRAPH APPROACHES 266 Sheng-Lung Peng and Yu-Wei Tsay 15.1 Introduction / 266 15.2 Similarity in the Graph Model / 268 15.3 Measuring Structural Similarity VIA MCES / 272 15.4 Protein Comparison VIA Graph Spectra / 279 15.5 Conclusion / 287 References / 287 16 STRUCTURAL DOMAINS IN PREDICTION OF BIOLOGICAL PROTEIN-PROTEIN INTERACTIONS 291 Mina Maleki, Michael Hall, and Luis Rueda 16.1 Introduction / 291 16.2 Structural Domains / 293 16.3 The Prediction Framework / 293 16.4 Feature Extraction and Prediction Properties / 294 16.5 Feature Selection / 299 16.6 Classification / 301 16.7 Evaluation and Analysis / 304 16.8 Results and Discussion / 304 16.9 Conclusion / 309 References / 310 V PATTERN RECOGNITION IN MICROARRAYS 315 17 CONTENT-BASED RETRIEVAL OF MICROARRAY EXPERIMENTS 317 Hasan O¢gul 17.1 Introduction / 317 17.2 Information Retrieval: Terminology and Background / 318 17.3 Content-Based Retrieval / 320 17.4 Microarray Data and Databases / 322 17.5 Methods for Retrieving Microarray Experiments / 324 17.6 Similarity Metrics / 327 17.7 Evaluating Retrieval Performance / 329 17.8 Software Tools / 330 17.9 Conclusion and Future Directions / 331 Acknowledgment / 332 References / 332 18 EXTRACTION OF DIFFERENTIALLY EXPRESSED GENES IN MICROARRAY DATA 335 Tiratha Raj Singh, Brigitte Vannier, and Ahmed Moussa 18.1 Introduction / 335 18.2 From Microarray Image to Signal / 336 18.3 Microarray Signal Analysis / 337 18.4 Algorithms for De Gene Selection / 339 18.5 Gene Ontology Enrichment and Gene Set Enrichment Analysis / 343 18.6 Conclusion / 345 References / 345 19 CLUSTERING AND CLASSIFICATION TECHNIQUES FOR GENE EXPRESSION PROFILE PATTERN ANALYSIS 347 Emanuel Weitschek, Giulia Fiscon, Valentina Fustaino, Giovanni Felici, and Paola Bertolazzi 19.1 Introduction / 347 19.2 Transcriptome Analysis / 348 19.3 Microarrays / 349 19.4 RNA-Seq / 351 19.5 Benefits and Drawbacks of RNA-Seq and Microarray Technologies / 353 19.6 Gene Expression Profile Analysis / 356 19.7 Real Case Studies / 364 19.8 Conclusions / 367 References / 368 20 MINING INFORMATIVE PATTERNS IN MICROARRAY DATA 371 Li Teng 20.1 Introduction / 371 20.2 Patterns with Similarity / 373 20.3 Conclusion / 391 References / 391 21 ARROW PLOT AND CORRESPONDENCE ANALYSIS MAPS FOR VISUALIZING THE EFFECTS OF BACKGROUND CORRECTION AND NORMALIZATION METHODS ON MICROARRAY DATA 394 Carina Silva, Adelaide Freitas, Sara Roque, and Lisete Sousa 21.1 Overview / 394 21.2 Arrow Plot / 399 21.3 Significance Analysis of Microarrays / 404 21.4 Correspondence Analysis / 405 21.5 Impact of the Preprocessing Methods / 407 21.6 Conclusions / 412 Acknowledgments / 413 References / 413 VI PATTERN RECOGNITION IN PHYLOGENETIC TREES 417 22 PATTERN RECOGNITION IN PHYLOGENETICS: TREES AND NETWORKS 419 David A. Morrison 22.1 Introduction / 419 22.2 Networks and Trees / 420 22.3 Patterns and Their Processes / 424 22.4 The Types of Patterns / 427 22.5 Fingerprints / 431 22.6 Constructing Networks / 433 22.7 Multi-Labeled Trees / 435 22.8 Conclusion / 436 References / 437 23 DIVERSE CONSIDERATIONS FOR SUCCESSFUL PHYLOGENETIC TREE RECONSTRUCTION: IMPACTS FROM MODEL MISSPECIFICATION, RECOMBINATION, HOMOPLASY, AND PATTERN RECOGNITION 439 Diego Mallo, Agustín Sánchez-Cobos, and Miguel Arenas 23.1 Introduction / 440 23.2 Overview on Methods and Frameworks for Phylogenetic Tree Reconstruction / 440 23.3 Influence of Substitution Model Misspecification on Phylogenetic Tree Reconstruction / 445 23.4 Influence of Recombination on Phylogenetic Tree Reconstruction / 446 23.5 Influence of Diverse Evolutionary Processes on Species Tree Reconstruction / 447 23.6 Influence of Homoplasy on Phylogenetic Tree Reconstruction: The Goals of Pattern Recognition / 449 23.7 Concluding Remarks / 449 Acknowledgments / 450 References / 450 24 AUTOMATED PLAUSIBILITY ANALYSIS OF LARGE PHYLOGENIES 457 David Dao, Tomás Flouri, and Alexandros Stamatakis 24.1 Introduction / 457 24.2 Preliminaries / 459 24.3 A Naïve Approach / 462 24.4 Toward a Faster Method / 463 24.5 Improved Algorithm / 467 24.6 Implementation / 473 24.7 Evaluation / 474 24.8 Conclusion / 479 Acknowledgment / 481 References / 481 25 A NEW FAST METHOD FOR DETECTING AND VALIDATING HORIZONTAL GENE TRANSFER EVENTS USING PHYLOGENETIC TREES AND AGGREGATION FUNCTIONS 483 Dunarel Badescu, Nadia Tahiri, and Vladimir Makarenkov 25.1 Introduction / 483 25.2 Methods / 485 25.3 Experimental Study / 491 25.4 Results and Discussion / 501 25.5 Conclusion / 502 References / 503 VII PATTERN RECOGNITION IN BIOLOGICAL NETWORKS 505 26 COMPUTATIONAL METHODS FOR MODELING BIOLOGICAL INTERACTION NETWORKS 507 Christos Makris and Evangelos Theodoridis 26.1 Introduction / 507 26.2 Measures/Metrics / 508 26.3 Models of Biological Networks / 511 26.4 Reconstructing and Partitioning Biological Networks / 511 26.5 PPI Networks / 513 26.6 Mining PPI Networks--Interaction Prediction / 517 26.7 Conclusions / 519 References / 519 27 BIOLOGICAL NETWORK INFERENCE AT MULTIPLE SCALES: FROM GENE REGULATION TO SPECIES INTERACTIONS 525 Andrej Aderhold, V Anne Smith, and Dirk Husmeier 27.1 Introduction / 525 27.2 Molecular Systems / 528 27.3 Ecological Systems / 528 27.4 Models and Evaluation / 529 27.5 Learning Gene Regulation Networks / 532 27.6 Learning Species Interaction Networks / 540 27.7 Conclusion / 550 References / 550 28 DISCOVERING CAUSAL PATTERNS WITH STRUCTURAL EQUATION MODELING: APPLICATION TO TOLL-LIKE RECEPTOR SIGNALING PATHWAY IN CHRONIC LYMPHOCYTIC LEUKEMIA 555 Athina Tsanousa, Stavroula Ntoufa, Nikos Papakonstantinou, Kostas Stamatopoulos, and Lefteris Angelis 28.1 Introduction / 555 28.2 Toll-Like Receptors / 557 28.3 Structural Equation Modeling / 560 28.4 Application / 566 28.5 Conclusion / 580 References / 581 29 ANNOTATING PROTEINS WITH INCOMPLETE LABEL INFORMATION 585 Guoxian Yu, Huzefa Rangwala, and Carlotta Domeniconi 29.1 Introduction / 585 29.2 Related Work / 587 29.3 Problem Formulation / 589 29.4 Experimental Setup / 592 29.5 Experimental Analysis / 596 29.6 Conclusions / 605 Acknowledgments / 606 References / 606 INDEX 609

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