Paul A. Gagniuc

Algorithms in Bioinformatics


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Discussions 7.7 Conclusions

      14  8 Detection of Motifs (I) 8.1 Introduction 8.2 DNA Motifs 8.3 Major Functions of DNA Motifs 8.4 Conclusions

      15  9 Representation of Motifs (II) 9.1 Introduction 9.2 The Training Data 9.3 A Visualization Function 9.4 The Alignment Matrix 9.5 Alphabet Detection 9.6 The Position-Specific Scoring Matrix (PSSM) Initialization 9.7 The Position Frequency Matrix (PFM) 9.8 The Position Probability Matrix (PPM) 9.9 The Position Weight Matrix (PWM) 9.10 The Background Model 9.11 The Consensus Sequence 9.12 Mutational Intolerance 9.13 From Motifs to PWMs 9.14 Pseudo-Counts and Negative Infinity 9.15 Conclusions

      16  10 The Motif Scanner (III) 10.1 Introduction 10.2 Looking for Signals 10.3 A Functional Scanner 10.4 The Meaning of Scores 10.5 Conclusions

      17  11 Understanding the Parameters (IV) 11.1 Introduction 11.2 Experimentation 11.3 Signal Discrimination 11.4 False-Positive Results 11.5 Sensitivity Adjustments 11.6 Beyond Bioinformatics 11.7 A Scanner That Uses a Known PWM 11.8 Signal Thresholds 11.9 Conclusions

      18  12 Dynamic Backgrounds (V) 12.1 Introduction 12.2 Toward a Scanner with Two PFMs 12.3 A Scanner with Two PFMs 12.4 Information and Background Frequencies on Score Values 12.5 Dynamic Background vs. Null Model 12.6 Conclusions

      19  13 Markov Chains: The Machine (I) 13.1 Introduction 13.2 Transition Matrices 13.3 Discrete Probability Detector 13.4 Markov Chains Generators 13.5 Conclusions

      20  14 Markov Chains: Log Likelihood (II) 14.1 Introduction 14.2 The Log-Likelihood Matrix 14.3 Interpretation and Use of the Log-Likelihood Matrix 14.4 Construction of a Markov Scanner 14.5 A Scanner That Uses a Known LLM 14.6 The Meaning of Scores 14.7 Beyond Bioinformatics 14.8 Conclusions

      21  15 Spectral Forecast (I) 15.1 Introduction 15.2 The Spectral Forecast Model 15.3 The Spectral Forecast Equation 15.4 The Spectral Forecast Inner Workings 15.5 Implementations 15.6 The Spectral Forecast Model for Predictions 15.7 Conclusions

      22  16 Entropy vs. Content (I) 16.1 Introduction 16.2 Information Entropy 16.3 Implementation 16.4 Information Content vs. Information Entropy 16.5 Conclusions

      23  17 Philosophical Transactions 17.1 Introduction 17.2 The Frame of Reference 17.3 Random vs. Pseudo-random 17.4 Random Numbers and Noise 17.5 Determinism and Chaos 17.6 Free Will and Determinism