
Algorithms in Bioinformatics
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Content
- Intro
- Preface
- Organization
- Abstracts
- Reference-free Compression of High Throughput Sequencing Data with a Probabilistic de Bruijn Graph
- Genome Scaffolding with PE-Contaminated Mate-Pair Libraries
- Network Properties of the Ensemble of RNA Structures
- Contents
- BicNET: Efficient Biclustering of Biological Networks to Unravel Non-Trivial Modules
- 1 Introduction
- 2 Background
- 3 Solution
- 3.1 Network Modules with Flexible Coherency
- 3.2 BicNET: Efficient Biclustering of Biological Networks
- 4 Results and Discussion
- 4.1 Results on Synthetic Data
- 4.2 Results on Real Data
- 5 Conclusions and Future Work
- References
- Simultaneous Optimization of both Node and Edge Conservation in Network Alignment via WAVE
- 1 Introduction
- 1.1 Motivation
- 1.2 Related Work
- 1.3 Our Contributions and Significance
- 2 Methods
- 2.1 Data
- 2.2 Combining Topological and Sequence Information Within NCF
- 2.3 Evaluation of Alignment Quality
- 2.4 Our Methodology
- 3 Results and Discussion
- 3.1 Comparison of Edge-Weighted and Edge-Unweighted Versions of WAVE
- 3.2 Comparison of Different Parameter Values Within WAVE
- 3.3 Comparison of Five NCF-AS Methods
- 3.4 Comparison of WAVE with Very Recent Methods
- 4 Concluding Remarks
- A Appendix
- A.1 Appendix Figures
- References
- The Topological Profile of a Model of Protein Network Evolution Can Direct Model Improvement
- 1 Introduction
- 2 Methods
- 2.1 The Evolutionary Model
- 2.2 The Empirical Network
- 2.3 Topological Measures Assessed
- 3 Results
- 3.1 Success of Driving Properties Towards the Empirical Topology
- 3.2 Non-Optimized Topological Properties that Trend Towards Empirical Values
- 3.3 Variability of Topological Measures
- 3.4 Correlation Among Topological Characteristics
- 3.5 Improving the Evolutionary Model
- 4 Conclusion
- References
- Algorithms for Regular Tree Grammar Network Search and Their Application to Mining Human-Viral Infection Patterns
- 1 Introduction
- 2 Regular Tree Grammars and Curry-Encoding
- 3 The RTG Network Parse-and-Search Problem
- 4 Algorithms for Solving Problem 2
- 4.1 Stage 1: Hypergraph Construction and Its Optimal Derivation
- 4.2 Stage 2: Computing K-Best Scoring Trees
- 5 Results
- 6 Discussion
- References
- Orthology Relation and Gene Tree Correction: Complexity Results
- 1 Introduction
- 2 Trees and Orthology Relations
- 2.1 Evolution of a Gene Family
- 2.2 Relation Graph
- 3 Relation Correction Problems
- 3.1 The Minimum Edge-Removal Consistency Problem
- 3.2 The Minimum Node-Removal Consistency Problem
- 4 Gene Tree Correction Problems
- 4.1 The Maximum Homology Correction Problem
- 4.2 The Maximum Clade Correction Problem
- 5 Algorithmic Avenues
- 6 Conclusion
- References
- Finding a Perfect Phylogeny from Mixed Tumor Samples
- 1 Introduction
- 2 Problem Formulation
- 3 A Characterization of Row-Conflict Graphs
- 4 Complexity Results
- 5 An Algorithm for the Case When No Column Is Contained in both Columns of a Pair of Conflicting Columns
- 6 Discussion
- References
- A Sub-quadratic Time and Space Complexity Solution for the Dated Tree Reconciliation Problem for Select Tree Topologies
- 1 Background
- 2 Methodology
- 2.1 The Number of Mapping Sites Required for Each Parasite Node
- 2.2 Space Complexity Reduction
- 2.3 Time Complexity Reduction
- 3 Results and Discussion
- 3.1 Analysis of Space Complexity Improvements (Synthetic Data)
- 3.2 Analysis of Time Complexity Improvements (Synthetic Data)
- 3.3 Time and Space Complexity Improvements for Biological Data
- References
- Maximum Parsimony Analysis of Gene Copy Number Changes
- 1 Introduction
- 2 Methods
- 2.1 The Rectilinear Steiner Minimum Tree (RSMT) Problem
- 2.2 The Maximum Parsimony Tree (MPT) Problem
- 2.3 From MPT to RSMT
- 3 Experimental Results
- 3.1 Real Cancer Datasets
- 3.2 Simulated Cancer Data
- 4 Discussion
- References
- Multiple-Ancestor Localization for Recently Admixed Individuals
- 1 Introduction
- 2 Materials and Methods
- 2.1 Estimation of Spatial Parameters from Training Data
- 2.2 Localization of Individuals of 1-Generation Admixture
- 2.3 A Spatial Model for Individuals of g-generations Admixture
- 2.4 Simulation Setup
- 2.5 Method Comparison
- 3 Results
- 3.1 Localization of Simulated 1-Generation Admixed Individuals
- 3.2 Localization of Real Europeans from the POPRES Dataset
- 3.3 Localization of Simulated g-generation Admixed Individuals
- 4 Discussion
- References
- Association Mapping for Compound Heterozygous Traits Using Phenotypic Distance and Integer Programming
- 1 Biological Background and CH-Model
- 1.1 A Formal Model of a CH-trait at a Single Gene
- 2 The Phenotypic Distance Problem
- 2.1 An ILP Formulation for the Phenotypic Distance Problem
- 3 Simulated Data
- 4 The Most Striking and Positive Empirical Results
- 4.1 Speeding Up the Computations for Non-causal Genes and Permuted Data
- References
- Semi-nonparametric Modeling of Topological Domain Formation from Epigenetic Data
- 1 Introduction
- 1.1 Additional Related Work
- 2 The nTDP Model
- 2.1 The Likelihood Function
- 2.2 Nonparametric Form of the Effect Functions
- 3 Optimal Algorithms for Training and Inference
- 3.1 Training
- 3.2 Training Extensions
- 3.3 Inferring Domains Using the Trained Model
- 4 Results
- 4.1 Experimental Setup
- 4.2 nTDP Finds a Small Subset of Modifications Predictive of TADs
- 4.3 Predicting TADs from Histone Marks in Human
- 4.4 Multiscale Analysis of the Predicted TADs
- 5 Conclusion
- References
- Scrible: Ultra-Accurate Error-Correction of Pooled Sequenced Reads
- 1 Introduction
- 2 Preliminaries
- 2.1 Pooling Design
- 2.2 Read Decoding
- 3 Methods
- 3.1 Indexing k-mers
- 3.2 Identification and Correction of Sequencing Errors
- 4 Experimental Results
- 4.1 Results on Synthetic Reads for the Rice Genome
- 4.2 Results on Real Reads from the Barley Genome
- References
- Jabba: Hybrid Error Correction for Long Sequencing Reads Using Maximal Exact Matches
- 1 Introduction
- 1.1 Related Work
- 2 Methods
- 2.1 Overview
- 2.2 Correction of the de Bruijn Graph
- 2.3 Aligning Reads to a de Bruijn Graph
- 3 Results Concerning Maximal Exact Matches
- 3.1 Coverage by Exact Regions
- 3.2 Occurrence of Exact Regions
- 3.3 Applications
- 4 Results
- 4.1 Data
- 4.2 Parameters
- 4.3 Evaluation Metrics
- 4.4 Evaluation
- References
- Optimizing Read Reversals for Sequence Compression
- 1 Introduction
- 2 Problem Taxonomy
- 3 Hardness Results
- 4 Approximation Algorithms
- 4.1 Approximations Based on TSP
- 4.2 Ordering with Reversals for Palindromic Value Functions
- 5 Experimental Results
- References
- Circular Sequence Comparison with q-grams
- 1 Introduction
- 2 Definitions and Properties
- 3 Algorithms
- 3.1 Algorithm hCSC: a Heuristic Algorithm
- 3.2 Algorithm saCSC: an Exact Suffix-Array-based Algorithm
- 4 Experimental Results
- 4.1 Accuracy
- 4.2 Time Performance
- 4.3 Application to Real Data
- 5 Final Remarks
- References
- Bloom Filter Trie -- A Data Structure for Pan-Genome Storage
- 1 Introduction
- 2 Existing Approaches
- 2.1 Data Structures
- 2.2 Software for Pan-Genome Storage
- 3 The Bloom Filter Trie
- 3.1 Uncompressed Container
- 3.2 Compressed Container
- 4 Operations Supported by the Bloom Filter Trie
- 4.1 Look-Up
- 4.2 Insertion
- 4.3 Color Compression
- 5 Traversing Successors and Predecessors
- 6 Evaluation
- 7 Conclusion
- References
- A Filtering Approach for Alignment-Free Biosequences Comparison with Mismatches
- 1 Introduction
- 2 Preliminaries
- 2.1 Related Work
- 3 The MissMax Algorithm
- 3.1 Initial Set Up: MaxCork(1)
- 3.2 Minimum MaxCork from the Previous Step
- 3.3 Potential Candidates from the Previous Step
- 3.4 Theoretical and Practical Considerations
- 4 Preliminary Experimental Analysis
- 5 Concluding Remarks
- References
- Models and Algorithms for Genome Rearrangement with Positional Constraints
- 1 Introduction
- 1.1 Genomes as Sets of Signed Integers
- 1.2 DCJ and Sorting DCJs
- 1.3 The Minimum Weighted Rearrangements Problem
- 1.4 Positional Constraints as Colored Adjacencies
- 1.5 Locality and the Adjacency Graph
- 1.6 A Positional Weight Function
- 2 Minimum Local Parsimonious Scenario
- 2.1 Colored Partitions
- 2.2 Even-length Paths
- 3 Conclusion
- References
- Sparse RNA Folding Revisited: Space-Efficient Minimum Free Energy Prediction
- 1 Introduction
- 2 Time and Space Efficient Computation of the MFE
- 2.1 Time and Space Efficient Bp-Based Folding
- 2.2 Time and Space Efficient Calculation of the MFE
- 2.3 The Difficulty of MFE Fold Reconstruction Compared to Bp-Based Folding
- 3 MFE Folding with Fold Reconstruction
- 3.1 Adding Trace Arrows
- 3.2 Avoiding Trace Arrows
- 3.3 Garbage Collecting Trace Arrows
- 3.4 Algorithm Summary
- 3.5 Complexity
- 4 Empirical Results
- 5 Conclusion and Future Work
- References
- A Sparsified Four-Russian Algorithm for RNA Folding
- 1 Introduction
- 2 Problem Definition and Basic Algorithm
- 2.1 Extending the Notation and Moving Towards a Vector by Vector Computation of
- 3 Sparsification of the SSF Algorithm
- 3.1 OCT and STEP Sub-instances of Sequence
- 4 On-demand Four Russians Speedup
- 5 Sparse Four-Russian Method
- 5.1 Condition for Sets of Split Points
- 5.2 Asymptotic Analysis of On-demand Lookup Tables Calculation
- 5.3 Empirical Results
- 5.4 Future Work
- References
- Higher Classification Accuracy of Short Metagenomic Reads by Discriminative Spaced k-mers
- 1 Introduction
- 2 Classification by Discriminative Spaced k-mers
- 2.1 Preliminaries
- 2.2 Discriminative Spaced k-mers
- 2.3 Selection of Optimal Spaced Seeds and Index Creation
- 3 Results
- 3.1 Datasets
- 3.2 Comparison with Other Tools
- 3.3 Classification Accuracy
- 3.4 Real Metagenomic Samples
- 3.5 Time and Space Complexity
- 4 Discussion
- References
- Graph-Theoretic Modelling of the Domain Chaining Problem
- 1 Introduction
- 2 Definitions and Notations
- 3 Results
- 4 Conclusion
- References
- Efficient Design of Compact Unstructured RNA Libraries Covering All k-mers
- 1 Introduction
- 2 Preliminaries
- 2.1 de Bruijn Graphs
- 2.2 Unstructured RNA Probes and Self-structured k-mers
- 2.3 Problems Definition
- 3 Methods
- 3.1 Approximation Algorithm Through the Minimum m-set Cover Problem
- 3.2 A Heuristic Greedy Algorithm Based on Random Walks in de Bruijn Graphs
- 3.3 NP-Hardness of the Minimum k-mer Coverage by -long Sequences Problem
- 4 Results
- 4.1 Traditional Methods Won't Solve Our Problem
- 4.2 A Theoretical Lower Bound for the Number of Oligos
- 4.3 Computational Results
- 4.4 Comparison to the Library Design of Ray et al.
- 5 Conclusion
- References
- Author Index
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