Franklin

Research in Computational Molecular Biology : 23rd Annual International Conference, RECOMB 2019, Washington, DC, USA, May 5-8, 2019, Proceedings / edited by Lenore J. Cowen.

Edition:
1st ed. 2019.
Publication:
Cham : Springer International Publishing : Imprint: Springer, 2019.
Series:
Computer Science (Springer-11645)
Lecture notes in computer science. Lecture notes in bioinformatics 11467
Lecture Notes in Bioinformatics ; 11467
Format/Description:
Book
1 online resource (XIV, 337 pages) : 146 illustrations, 67 illustrations in color.
Subjects:
Bioinformatics.
Information storage and retrieval.
Computer arithmetic and logic units.
Artificial intelligence.
Computer science-Mathematics.
Local subjects:
Computational Biology/Bioinformatics. (search)
Information Storage and Retrieval. (search)
Arithmetic and Logic Structures. (search)
Artificial Intelligence. (search)
Mathematics of Computing. (search)
System Details:
text file PDF
Summary:
This book constitutes the proceedings of the 23rd Annual Conference on Research in Computational Molecular Biology, RECOMB 2019, held in Washington, DC, USA, in April 2019. The 17 extended and 20 short abstracts presented were carefully reviewed and selected from 175 submissions. The short abstracts are included in the back matter of the volume. The papers report on original research in all areas of computational molecular biology and bioinformatics.
Contents:
An Efficient, Scalable and Exact Representation of High-Dimensional Color Information Enabled Via de Bruijn Graph Search
Identifying Clinical Terms in Free-Text Notes Using Ontology-Guided Machine Learning
ModHMM: A Modular Supra-Bayesian Genome Segmentation Method
Learning Robust Multi-Label Sample Specific Distances for Identifying HIV-1 Drug Resistance
MethCP: Differentially Methylated Region Detection with Change Point Models
On the Complexity of Sequence to Graph Alignment
Minimization-Aware Recursive K* (MARK*): A Novel, Provable Algorithm that Accelerates Ensemble-based Protein Design and Provably Approximates the Energy Landscape
Sparse Binary Relation Representations for Genome Graph Annotation
How Many Subpopulations is Too Many? Exponential Lower Bounds for Inferring Population Histories
Efficient Construction of a Complete Index for Pan-Genomics Read Alignment
Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data
OMGS: Optical Map-based Genome Scaffolding
Fast Approximation of Frequent k-mers and Applications to Metagenomics
De Novo Clustering of Long-Read Transcriptome Data Using a Greedy, Quality-Value Based Algorithm
A Sticky Multinomial Mixture Model of Strand-Coordinated Mutational Processes in Cancer
Disentangled Representations of Cellular Identity
RENET: A Deep Learning Approach for Extracting Gene-Disease Associations from Literature
APPLES: Fast Distance Based Phylogenetic Placement
De Novo Peptide Sequencing Reveals a Vast Cyclopeptidome in Human Gut and Other environments
Biological Sequence Modeling with Convolutional Kernel Networks
Dynamic Pseudo-Time Warping of Complex Single-Cell Trajectories
netNMF-sc: A Network Regularization Algorithm for Dimensionality Reduction and Imputation of Single-Cell Expression Data
Geometric Sketching of Single-Cell Data Preserves Transcriptional Structure
Sketching Algorithms for Genomic Data Analysis and Querying in a Secure Enclave
Mitigating Data Scarcity in Protein Binding Prediction Using Meta-Learning
Efficient Estimation and Applications of Cross-Validated Genetic Predictions
Inferring Tumor Evolution from Longitudinal Samples
Scalable Multi-Component Linear Mixed Models with Application to SNP Heritability Estimation
A Note on Computing Interval Overlap Statistics
Distinguishing Biological from Technical Sources of Variation by Leveraging Multiple Methylation Datasets
GRep: Gene Set Representation via Gaussian Embedding
Accurate Sub-Population Detection and Mapping Across Single Cell Experiments with PopCorn
Fast Estimation of Genetic Correlation for Biobank-Scale Data
Distance-Based Protein Folding Powered by Deep Learning
Comparing 3D Genome Organization in Multiple Species Using Phylo-HMRF
Towards a Post-Clustering Test for Didderential Expression
AdaFDR: a Fast, Powerful and Covariate-Adaptive Approach for Multiple Hypothesis Testing.
Contributor:
Cowen, Lenore J. editor., Editor,
SpringerLink (Online service)
Contained In:
Springer eBooks
Other format:
Printed edition:
Printed edition:
ISBN:
978-3-030-17083-7
9783030170837
Publisher Number:
10.1007/978-3-030-17083-7 doi
Access Restriction:
Restricted for use by site license.
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