Algorithms for Computational Biology

6th International Conference, AlCoB 2019, Berkeley, CA, USA, May 28–30, 2019, Proceedings

Häftad, Engelska, 2019

Av Ian Holmes, Carlos Martín-Vide, Miguel A. Vega-Rodríguez, Carlos Martin-Vide, Miguel A. Vega-Rodriguez

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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.

Produktinformation

Utgivningsdatum2019-04-13
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieLecture Notes in Bioinformatics
Antal sidor225
FörlagSpringer Nature Switzerland AG
ISBN9783030181734

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Systemvetenskap och AI inom Data och it
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Invited Talk.- New Divide-and-Conquer Techniques for Large-Scale Phylogenetic Estimation.- Biological Networks and Graph Algorithms.- New Polynomial-Time Algorithm around the Scaffolding Problem.- Enumerating Dominant Pathways in Biological Networks by Information Flow Analysis.- Comparing Different Graphlet Measures for Evaluating Network Model Fits to BioGRID PPI Networks.- Graph-Theoretic Partitioning of RNAs and Classification of Pseudoknots.- PathRacer: Racing Profile HMM Paths on Assembly Graph.- Genome Rearrangement, Assembly and Classification.- A Uniform Theory of Adequate Subgraphs for the Genome Median, Halving, and Aliquoting Problems.- Lightweight Metagenomic Classification via eBWT.- MULKSG: MULtiple K Simultaneous Graph Assembly.- Counting Sorting Scenarios and Intermediate Genomes for the Rank Distance.- Generalizations of the Genomic Rank Distance to Indels.- Sequence Analysis, Phylogenetics and Other Biological Processes.- Using INC within Divide-and-Conquer Phylogeny Estimation.- Predicting Methylation from Sequence and Gene Expression Using Deep Learning with Attention.- A Mathematical Model for Enhancer Activation Kinetics During Cell Differentiation.- Transcript Abundance Estimation and the Laminar Packing Problem.- Efficient Algorithms for Finding Edit-Distance Based Motifs.