Pattern Recognition in Computational Molecular Biology (eBook, ePUB)
Techniques and Approaches
Alle Infos zum eBook verschenken
Pattern Recognition in Computational Molecular Biology (eBook, ePUB)
Techniques and Approaches
- Format: ePub
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Hier können Sie sich einloggen
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern…mehr
- Geräte: eReader
- mit Kopierschutz
- eBook Hilfe
- Größe: 35.87MB
- Wladyslaw HomendaPattern Recognition (eBook, ePUB)109,99 €
- Ulisses M. Braga NetoError Estimation for Pattern Recognition (eBook, ePUB)118,99 €
- Pradipta MajiRough-Fuzzy Pattern Recognition (eBook, ePUB)101,99 €
- Amit KonarEmotion Recognition (eBook, ePUB)118,99 €
- Basel Abu-JamousIntegrative Cluster Analysis in Bioinformatics (eBook, ePUB)101,99 €
- Supervised and Unsupervised Pattern Recognition (eBook, ePUB)51,95 €
- King-Sun FuApplications of Pattern Recognition (eBook, ePUB)148,95 €
-
-
-
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
- Produktdetails
- Verlag: John Wiley & Sons
- Seitenzahl: 656
- Erscheinungstermin: 24. Dezember 2015
- Englisch
- ISBN-13: 9781119078869
- Artikelnr.: 44447401
- Verlag: John Wiley & Sons
- Seitenzahl: 656
- Erscheinungstermin: 24. Dezember 2015
- Englisch
- ISBN-13: 9781119078869
- Artikelnr.: 44447401
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
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