Algorithms for computational biology : 6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28-30, 2019, Proceedings / Ian Holmes, Carlos Martín-Vide, Miguel A. Vega-Rodríguez, editors.

International conference proceedings.

Includes bibliographical references and author index.

Online resource; title from PDF title page (SpringerLink, viewed June 24, 2019).

Intro; Preface; Organization; Abstracts of Invited Talks; Exploring Phenotypic Heterogeneity Across Tissues and Conditions with Network-Based Approaches; New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation#x8E;1#x90;; Contents; Invited Talk; New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation; 1 Introduction; 2 Phylogeny Estimation; 2.1 Gene Tree Estimation; 2.2 Species Tree Estimation; 2.3 Divide-and-Conquer Strategies; 3 Disjoint Tree Merger; 3.1 The DTM Problem; 3.2 NJMerge; 3.3 Constrained INC; 4 Pipelines Using DTM Methods; 4.1 Overview

4.2 Theoretical Guarantees4.3 Empirical Results; 4.4 Discussion; 5 Conclusions; References; Biological Networks and Graph Algorithms; New Polynomial-Time Algorithm Around the Scaffolding Problem; 1 Introduction; 2 Notation and Problem Description; 3 Feasibility; 3.1 Feasability Function; 4 Approximation Result; 4.1 Notations and Definitions; 4.2 Optimization; 4.3 Algorithm; 5 Conclusion; A Appendix; A.1 Algorithms; References; Enumerating Dominant Pathways in Biological Networks by Information Flow Analysis; 1 Introduction; 2 Information Flow in Biological Networks

2.1 Network Implementation2.2 Network Simulation; 3 A Case Study: Escherichia coli Transcription Network; 4 Discussion; References; Comparing Different Graphlet Measures for Evaluating Network Model Fits to BioGRID PPI Networks; 1 Introduction; 1.1 Graphlets; 1.2 Graphlet-Based Network Comparison Measures; 1.3 Models; 1.4 Comparing Models to Data; 1.5 Our Contribution; 2 Methods; 3 Results; 3.1 Assessing Quality of Each Measure; 3.2 Assessment of Fits to PPIs by Graphlet-Based Measures; 3.3 Mixed Agreement Across Measures; 4 Fit of PPI Networks from the 2018 Update of the IID Database

5 Discussion and ConclusionReferences; Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots; 1 Introduction; 2 Background; 2.1 Biological and Topological Definitions; 2.2 Graph Partitioning Algorithm; 3 Classification of Pseudoknots as Either Recursive or Non-recursive and Identification of Each Recursive Region; 4 Conclusions and Ongoing Work; References; PathRacer: Racing Profile HMM Paths on Assembly Graph; 1 Introduction; 2 Methods; 2.1 General Definitions; 2.2 Event Graph; 2.3 Top(1) Path Problem via Event Graph

2.4 Dynamic Programming Algorithm for Best Path Extraction2.5 From Top(1) to Top(k); 2.6 Collapsing Event Graph; 2.7 Alignment Algorithm: Collapsed Event Graph Construction; 2.8 Implementation and Heuristics; 3 Results; 3.1 23S Search in E. coli str. K12 Assembly; 3.2 16S Components of SYNTH Mock Metagenome Dataset; 3.3 Urban Wastewater Metagenome; 3.4 PathRacer and MegaGTA Running Time and Memory Consumption; 4 Conclusion; References; Genome Rearrangement, Assembly and Classification; A Uniform Theory of Adequate Subgraphs for the Genome Median, Halving, and Aliquoting Problems

This book constitutes the proceedings of the 6th InternationalConference on Algorithms for Computational Biology, AlCoB 2019, held in Berkeley, CA, USA, in May 2019. The 15 full papers presented together with 1 invited paper were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: Biological networks and graph algorithms; genome rearrangement, assembly and classification; sequence analysis, phylogenetics and other biological processes.