Normal view MARC view ISBD view

Research in Computational Molecular Biology : 18th Annual International Conference, RECOMB 2014, Pittsburgh, PA, USA, April 2-5, 2014, Proceedings.

By: Hutchison, David.
Contributor(s): Kanade, Takeo | Kittler, Josef.
Material type: TextTextSeries: eBooks on Demand.Publisher: Cham : Springer International Publishing AG, z.Hd. Alexander Grossmann, 2014Copyright date: ©2014Description: 1 online resource (480 pages).Content type: text Media type: computer Carrier type: online resourceISBN: 9783319052694.Subject(s): Computational biology-Congresses | Bioinformatics-Congresses | Biomathematics-Congresses | Molekulare Bioinformatik.-gndGenre/Form: Electronic books.Additional physical formats: Print version:: Research in Computational Molecular Biology : 18th Annual International Conference, RECOMB 2014, Pittsburgh, PA, USA, April 2-5, 2014, ProceedingsDDC classification: 610.285 LOC classification: QH506 .R436 2014Online resources: Click here to view this ebook.
Contents:
Intro -- Preface -- Organization -- Table of Contents -- Tractatus: An Exact and Subquadratic Algorithm for Inferring Identical-by-Descent Multi-shared Haplotype Tracts -- 1 Introduction -- 1.1 Li-Stephens PAC-Likelihood Model and the O(m2n) Time Bound -- 1.2 Identical-by-Descent Haplotype Tracts -- 1.3 Prior Work -- 2 Methods -- 2.1 The Tractatus Model -- 2.2 The Tractatus Algorithm without Errors -- 2.3 The Tractatus Algorithm with Errors and Allele Mismatches -- 2.4 Extensions for Homozygous Haplotypes -- 3 Results -- 3.1 Tractatus vs. Pairwise Algorithm Runtimes -- 3.2 False Positive Rates -- 3.3 Power -- 3.4 Homozygous Haplotypes in Autism GWAS Data -- 4 Discussion -- 5 Conclusions -- References -- HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data -- 1 Background -- 2 Method -- 3 Results -- References -- Changepoint Analysis for Efficient Variant Calling -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Maximum Likelihood Estimation -- 3.2 Augmented Likelihood -- 3.3 Change Point Detection -- 3.4 Identification of High-Complexity Regions -- 3.5 Integrated Variant Calling Algorithm -- 4 Results -- 4.1 Datasets and Evaluation -- 4.2 Accuracy -- 4.3 Computational Performance -- 4.4 Properties of CAGe Regions -- 5 Discussion -- References -- On the Representation of de Bruijn Graphs -- 1 Introduction -- 2 Previous Work -- 3 Preliminaries -- 4 Navigational Data Structures -- 5 Navigational Data Structure Lower Bound for de Bruijn Graphs -- 6 Linear de Bruijn Graphs -- 7 Data Structure for Representing a de Bruijn Graph in Small Space (DBGFM) -- 8 Algorithm to Enumerate the Maximal Simple Paths of a de Bruijn Graph in LowMemory (BCALM) -- 9 Results -- 10 Conclusion -- References -- Exact Learning of RNA Energy Parameters from Structure -- 1 Introduction -- 2 Methods -- 2.1 Preliminaries.
2.2 Learnability of Energy Parameters -- 2.3 Necessary and Sufficient Condition for Learnability -- 2.4 Compatible Training Set -- 2.5 NP-hardness of Maximal Compatible Subset -- 2.6 Randomized Greedy Algorithm -- 3 Results -- 4 Discussion -- References -- An Alignment-Free Regression Approach for Estimating Allele-Specific Expression Using RNA-Seq Data -- 1 Introduction -- 2 Approach -- 2.1 Notation -- 2.2 Regression Model -- 3 Methods -- 3.1 Synthetic Data -- 3.2 Real Data -- 3.3 Selecting Candidate Transcripts -- 3.4 Coordinate Descent -- 4 Results -- 4.1 Synthetic Data Results -- 4.2 Real Data Results -- 4.3 Speed and Memory -- 5 Discussion -- References -- The Generating Function Approach for Peptide Identification in Spectral Networks -- 1 Introduction -- 2 Methods -- 2.1 Spectral Probabilities and Notation -- 2.2 Pairing of Spectra -- 2.3 Star Probabilities -- 2.4 Processing Real Spectra -- 2.5 Generating Candidate PSMs -- 3 Results -- 4 Discussion -- References -- Decoding Coalescent Hidden Markov Models in Linear Time -- 1 Introduction -- 2 Linear-Time Computation of the Forward and Backward Probabilities -- 2.1 A Linear-Time Forward Algorithm -- 2.2 A Linear-Time Backward Algorithm -- 3 Linear-Time EM via an Augmented HMM -- 3.1 The Standard EM Algorithm with -- 3.2 A Linear-Time EM Algorithm -- 4 Results -- 5 Discussion -- References -- AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application -- 1 Introduction -- 2 The AptaCluster Algorithm -- 3 Results of Application to HT-SELEX Experiment for IL-10RA -- 3.1 Validating Clustering Results -- 3.2 Distribution of Aptamers within Clusters -- 3.3 Frequency Counts versus Binding Affinity -- 4 Conclusions and Discussion -- 5 Materials and Methods -- 5.1 Dataset Description -- 5.2 Implementation Details -- 5.3 Parameters -- 5.4 HT-SELEX Experiment -- References.
Learning Sequence Determinants of Protein: Protein Interaction Specificity with Sparse Graphical Models -- 1 Introduction -- 2 Methods -- 2.1 A Graphical Model of Binding Free Energy -- 2.2 Training Objective -- 2.3 Block-Sparse Regularization -- 2.4 Learning Algorithms -- 3 Results -- 3.1 ΔG Prediction -- 3.2 Model Analysis -- 3.3 From Sequence Determinants to Sequence Design -- 4 Discussion and Conclusion -- References -- On Sufficient Statistics of Least-Squares Superposition of Vector Sets -- 1 Introduction -- 2 Orthogonal Superposition -- 3 Sufficient Statistics -- 4 Updating Sufficient Statistics -- 4.1 Addition Operation on Vector Sets Using Sufficient Statistics -- 4.2 Deletion Operation of Vector Sets Using Sufficient Statistics -- 5 Computing the r.m.s.d. from Updated Sufficient Statistics -- 6 Experiments -- 7 Conclusion -- References -- IDBA-MTP: A Hybrid MetaTranscriptomic Assembler Based on Protein Information -- 1 Introduction -- 2 Methodology -- 2.1 Dynamic Programming -- 2.2 Seed-and-Extend Heuristic -- 2.3 Preventing Redundant mRNAs -- 3 Experiments -- 3.1 Low Abundance mRNAs -- 3.2 mRNAs with Different Abundances -- 3.3 Real Metatranscriptomic Data -- 4 Conclusions -- References -- MRFalign: Protein Homology Detection through Alignment of Markov Random Fields -- References -- An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding -- References -- PASTA: Ultra-Large Multiple Sequence Alignment -- 1 Introduction and Motivation -- 2 PASTA -- 3 Experimental Setup -- 4 Results -- 5 Discussion and Future Work -- 6 Conclusions -- References -- Fast Flux Module Detection Using Matroid Theory -- 1 Introduction -- 1.1 Definitions and Preliminaries -- 2 Methods -- 2.1 Finding Modules Efficiently -- 2.2 Visualization -- 3 Results -- 3.1 Runtime of Module Finding -- 3.2 Visualization -- 4 Discussion.
4.1 Enumeration of Optimal-Yield Pathways -- 4.2 Modularity under Different Growth-Conditions -- 4.3 Applications Outside Metabolic Networks -- 4.4 Conclusion -- Authors Contributions -- References -- Building a Pangenome Reference for a Population -- 1 Introduction -- 2 Results -- 2.1 The Pangenome Reference Problem -- 2.2 NP-Hardness of the Pangenome Reference Problem -- 2.3 Algorithms for the Pangenome Reference Problem -- 2.4 Simulation Experiments -- 2.5 Creating a Pangenome Visualisation for the Major -- 3 Discussion and Conclusion -- References -- CSAX: Characterizing Systematic Anomalies in eXpression Data -- 1 Introduction -- 2 DataandMethods -- 2.1 Compendium of Microarray Anomaly Detection Data Sets -- 2.2 A New Method for Expression Anomaly Detection -- 2.3 Evaluating Anomaly Detection Methods -- 3 Results -- 3.1 Detection and Characterization of Anomalous Samples -- 3.2 Characterizing Heterogeneity through Anomaly Detection -- 3.3 How Hard Is an Anomaly Detection Task? -- 4 Discussion -- References -- WhatsHap: Haplotype Assembly for Future-Generation Sequencing Reads -- 1 Introduction -- 2 The Minimum Error Correction (MEC) Problem -- 3 A Dynamic Programming Algorithm for wMEC -- 4 Experimental Results -- 5 Conclusions and Further Work -- References -- Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data -- 1 Introduction -- 1.1 Previous Work -- 1.2 Contributions -- 2 Methods and Algorithms -- 2.1 Model and Problem Definition -- 2.2 Conditions for Reconstruction with Errors -- 2.3 Algorithm -- 3 Experimental Results -- 3.1 Simulated Data -- 3.2 Cancer Data -- 4 Conclusions -- References -- dipSPAdes: Assembler for Highly Polymorphic Diploid Genomes -- 1 Introduction -- 2 Definitions -- 3 Methods -- 3.1 Motivation -- 3.2 Polymorphism Masking -- 3.3 Consensus Overlap Graph.
3.4 Haplotype Assembly -- 3.5 dipSPAdes Algorithm -- 4 Results -- References -- An Exact Algorithm to Compute the DCJ Distance for Genomes with Duplicate Genes -- 1 Introduction -- 2 Problem Statement -- 3 ILP for the Maximum Cycle Decomposition Problem -- 4 Fixing Cycles of Length Two -- 5 Experimental Results -- 5.1 Simulation Results -- 5.2 Application to Orthology Assignment -- 6 Conclusion -- References -- HIT'nDRIVE: Multi-driver Gene Prioritization Based on Hitting Time -- 1 Introduction -- 2 HIT'nDRIVE Framework -- 2.1 Estimating Hitting Time on a Protein-Protein Interaction (PPI) Network -- 2.2 Estimating Multi-source Hitting Time via Single-Source Hitting Times -- 3 Reformulation of RWFL as aWeightedMulti-set Cover Problem -- 3.1 An ILP Formulation forWMSC -- 4 Evaluation Framework -- 5 Experiments -- 6 Conclusion and Future Work -- References -- Modeling Mutual Exclusivity of Cancer Mutations -- References -- Viral Quasispecies Assembly via Maximal Clique Enumeration -- Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency -- 1 Introduction -- 1.1 Multi-label Correlated Protein Function Prediction -- 1.2 Data-Knowledge Consistency and Our Motivations -- 1.3 Notations and Problem Formalization -- 2 Formulation of Function Category Correlations -- 3 The Maximization of Data-Knowledge Consistency (MDKC) Approach -- 3.1 Optimization Framework of the MDKC Approach -- 3.2 Computational Algorithm of MDKC Approach -- 4 Results and Discussion -- 4.1 Evaluation on Protein Sequence Data -- 4.2 Evaluation on Integrated Biological Data -- 5 Conclusions -- References -- Bayesian Multiple Protein Structure Alignment -- 1 Introduction -- 2 A Probabilistic Model for Protein Structure Families -- 3 Bayesian Multiple Alignment and MCMC Sampling -- 4 Results -- 5 Discussion -- References.
Gene-Gene Interactions Detection Using a Two-Stage Model.
Tags from this library: No tags from this library for this title. Log in to add tags.
Item type Current location Call number URL Status Date due Barcode
Electronic Book UT Tyler Online
Online
QH506 .R436 2014 (Browse shelf) https://ebookcentral.proquest.com/lib/uttyler/detail.action?docID=3101133 Available EBC3101133

Intro -- Preface -- Organization -- Table of Contents -- Tractatus: An Exact and Subquadratic Algorithm for Inferring Identical-by-Descent Multi-shared Haplotype Tracts -- 1 Introduction -- 1.1 Li-Stephens PAC-Likelihood Model and the O(m2n) Time Bound -- 1.2 Identical-by-Descent Haplotype Tracts -- 1.3 Prior Work -- 2 Methods -- 2.1 The Tractatus Model -- 2.2 The Tractatus Algorithm without Errors -- 2.3 The Tractatus Algorithm with Errors and Allele Mismatches -- 2.4 Extensions for Homozygous Haplotypes -- 3 Results -- 3.1 Tractatus vs. Pairwise Algorithm Runtimes -- 3.2 False Positive Rates -- 3.3 Power -- 3.4 Homozygous Haplotypes in Autism GWAS Data -- 4 Discussion -- 5 Conclusions -- References -- HapTree: A Novel Bayesian Framework for Single Individual Polyplotyping Using NGS Data -- 1 Background -- 2 Method -- 3 Results -- References -- Changepoint Analysis for Efficient Variant Calling -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Maximum Likelihood Estimation -- 3.2 Augmented Likelihood -- 3.3 Change Point Detection -- 3.4 Identification of High-Complexity Regions -- 3.5 Integrated Variant Calling Algorithm -- 4 Results -- 4.1 Datasets and Evaluation -- 4.2 Accuracy -- 4.3 Computational Performance -- 4.4 Properties of CAGe Regions -- 5 Discussion -- References -- On the Representation of de Bruijn Graphs -- 1 Introduction -- 2 Previous Work -- 3 Preliminaries -- 4 Navigational Data Structures -- 5 Navigational Data Structure Lower Bound for de Bruijn Graphs -- 6 Linear de Bruijn Graphs -- 7 Data Structure for Representing a de Bruijn Graph in Small Space (DBGFM) -- 8 Algorithm to Enumerate the Maximal Simple Paths of a de Bruijn Graph in LowMemory (BCALM) -- 9 Results -- 10 Conclusion -- References -- Exact Learning of RNA Energy Parameters from Structure -- 1 Introduction -- 2 Methods -- 2.1 Preliminaries.

2.2 Learnability of Energy Parameters -- 2.3 Necessary and Sufficient Condition for Learnability -- 2.4 Compatible Training Set -- 2.5 NP-hardness of Maximal Compatible Subset -- 2.6 Randomized Greedy Algorithm -- 3 Results -- 4 Discussion -- References -- An Alignment-Free Regression Approach for Estimating Allele-Specific Expression Using RNA-Seq Data -- 1 Introduction -- 2 Approach -- 2.1 Notation -- 2.2 Regression Model -- 3 Methods -- 3.1 Synthetic Data -- 3.2 Real Data -- 3.3 Selecting Candidate Transcripts -- 3.4 Coordinate Descent -- 4 Results -- 4.1 Synthetic Data Results -- 4.2 Real Data Results -- 4.3 Speed and Memory -- 5 Discussion -- References -- The Generating Function Approach for Peptide Identification in Spectral Networks -- 1 Introduction -- 2 Methods -- 2.1 Spectral Probabilities and Notation -- 2.2 Pairing of Spectra -- 2.3 Star Probabilities -- 2.4 Processing Real Spectra -- 2.5 Generating Candidate PSMs -- 3 Results -- 4 Discussion -- References -- Decoding Coalescent Hidden Markov Models in Linear Time -- 1 Introduction -- 2 Linear-Time Computation of the Forward and Backward Probabilities -- 2.1 A Linear-Time Forward Algorithm -- 2.2 A Linear-Time Backward Algorithm -- 3 Linear-Time EM via an Augmented HMM -- 3.1 The Standard EM Algorithm with -- 3.2 A Linear-Time EM Algorithm -- 4 Results -- 5 Discussion -- References -- AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application -- 1 Introduction -- 2 The AptaCluster Algorithm -- 3 Results of Application to HT-SELEX Experiment for IL-10RA -- 3.1 Validating Clustering Results -- 3.2 Distribution of Aptamers within Clusters -- 3.3 Frequency Counts versus Binding Affinity -- 4 Conclusions and Discussion -- 5 Materials and Methods -- 5.1 Dataset Description -- 5.2 Implementation Details -- 5.3 Parameters -- 5.4 HT-SELEX Experiment -- References.

Learning Sequence Determinants of Protein: Protein Interaction Specificity with Sparse Graphical Models -- 1 Introduction -- 2 Methods -- 2.1 A Graphical Model of Binding Free Energy -- 2.2 Training Objective -- 2.3 Block-Sparse Regularization -- 2.4 Learning Algorithms -- 3 Results -- 3.1 ΔG Prediction -- 3.2 Model Analysis -- 3.3 From Sequence Determinants to Sequence Design -- 4 Discussion and Conclusion -- References -- On Sufficient Statistics of Least-Squares Superposition of Vector Sets -- 1 Introduction -- 2 Orthogonal Superposition -- 3 Sufficient Statistics -- 4 Updating Sufficient Statistics -- 4.1 Addition Operation on Vector Sets Using Sufficient Statistics -- 4.2 Deletion Operation of Vector Sets Using Sufficient Statistics -- 5 Computing the r.m.s.d. from Updated Sufficient Statistics -- 6 Experiments -- 7 Conclusion -- References -- IDBA-MTP: A Hybrid MetaTranscriptomic Assembler Based on Protein Information -- 1 Introduction -- 2 Methodology -- 2.1 Dynamic Programming -- 2.2 Seed-and-Extend Heuristic -- 2.3 Preventing Redundant mRNAs -- 3 Experiments -- 3.1 Low Abundance mRNAs -- 3.2 mRNAs with Different Abundances -- 3.3 Real Metatranscriptomic Data -- 4 Conclusions -- References -- MRFalign: Protein Homology Detection through Alignment of Markov Random Fields -- References -- An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding -- References -- PASTA: Ultra-Large Multiple Sequence Alignment -- 1 Introduction and Motivation -- 2 PASTA -- 3 Experimental Setup -- 4 Results -- 5 Discussion and Future Work -- 6 Conclusions -- References -- Fast Flux Module Detection Using Matroid Theory -- 1 Introduction -- 1.1 Definitions and Preliminaries -- 2 Methods -- 2.1 Finding Modules Efficiently -- 2.2 Visualization -- 3 Results -- 3.1 Runtime of Module Finding -- 3.2 Visualization -- 4 Discussion.

4.1 Enumeration of Optimal-Yield Pathways -- 4.2 Modularity under Different Growth-Conditions -- 4.3 Applications Outside Metabolic Networks -- 4.4 Conclusion -- Authors Contributions -- References -- Building a Pangenome Reference for a Population -- 1 Introduction -- 2 Results -- 2.1 The Pangenome Reference Problem -- 2.2 NP-Hardness of the Pangenome Reference Problem -- 2.3 Algorithms for the Pangenome Reference Problem -- 2.4 Simulation Experiments -- 2.5 Creating a Pangenome Visualisation for the Major -- 3 Discussion and Conclusion -- References -- CSAX: Characterizing Systematic Anomalies in eXpression Data -- 1 Introduction -- 2 DataandMethods -- 2.1 Compendium of Microarray Anomaly Detection Data Sets -- 2.2 A New Method for Expression Anomaly Detection -- 2.3 Evaluating Anomaly Detection Methods -- 3 Results -- 3.1 Detection and Characterization of Anomalous Samples -- 3.2 Characterizing Heterogeneity through Anomaly Detection -- 3.3 How Hard Is an Anomaly Detection Task? -- 4 Discussion -- References -- WhatsHap: Haplotype Assembly for Future-Generation Sequencing Reads -- 1 Introduction -- 2 The Minimum Error Correction (MEC) Problem -- 3 A Dynamic Programming Algorithm for wMEC -- 4 Experimental Results -- 5 Conclusions and Further Work -- References -- Simultaneous Inference of Cancer Pathways and Tumor Progression from Cross-Sectional Mutation Data -- 1 Introduction -- 1.1 Previous Work -- 1.2 Contributions -- 2 Methods and Algorithms -- 2.1 Model and Problem Definition -- 2.2 Conditions for Reconstruction with Errors -- 2.3 Algorithm -- 3 Experimental Results -- 3.1 Simulated Data -- 3.2 Cancer Data -- 4 Conclusions -- References -- dipSPAdes: Assembler for Highly Polymorphic Diploid Genomes -- 1 Introduction -- 2 Definitions -- 3 Methods -- 3.1 Motivation -- 3.2 Polymorphism Masking -- 3.3 Consensus Overlap Graph.

3.4 Haplotype Assembly -- 3.5 dipSPAdes Algorithm -- 4 Results -- References -- An Exact Algorithm to Compute the DCJ Distance for Genomes with Duplicate Genes -- 1 Introduction -- 2 Problem Statement -- 3 ILP for the Maximum Cycle Decomposition Problem -- 4 Fixing Cycles of Length Two -- 5 Experimental Results -- 5.1 Simulation Results -- 5.2 Application to Orthology Assignment -- 6 Conclusion -- References -- HIT'nDRIVE: Multi-driver Gene Prioritization Based on Hitting Time -- 1 Introduction -- 2 HIT'nDRIVE Framework -- 2.1 Estimating Hitting Time on a Protein-Protein Interaction (PPI) Network -- 2.2 Estimating Multi-source Hitting Time via Single-Source Hitting Times -- 3 Reformulation of RWFL as aWeightedMulti-set Cover Problem -- 3.1 An ILP Formulation forWMSC -- 4 Evaluation Framework -- 5 Experiments -- 6 Conclusion and Future Work -- References -- Modeling Mutual Exclusivity of Cancer Mutations -- References -- Viral Quasispecies Assembly via Maximal Clique Enumeration -- Correlated Protein Function Prediction via Maximization of Data-Knowledge Consistency -- 1 Introduction -- 1.1 Multi-label Correlated Protein Function Prediction -- 1.2 Data-Knowledge Consistency and Our Motivations -- 1.3 Notations and Problem Formalization -- 2 Formulation of Function Category Correlations -- 3 The Maximization of Data-Knowledge Consistency (MDKC) Approach -- 3.1 Optimization Framework of the MDKC Approach -- 3.2 Computational Algorithm of MDKC Approach -- 4 Results and Discussion -- 4.1 Evaluation on Protein Sequence Data -- 4.2 Evaluation on Integrated Biological Data -- 5 Conclusions -- References -- Bayesian Multiple Protein Structure Alignment -- 1 Introduction -- 2 A Probabilistic Model for Protein Structure Families -- 3 Bayesian Multiple Alignment and MCMC Sampling -- 4 Results -- 5 Discussion -- References.

Gene-Gene Interactions Detection Using a Two-Stage Model.

Description based on publisher supplied metadata and other sources.

There are no comments for this item.

Log in to your account to post a comment.