Research in Computational Molecular Biology

1. Front Matter

   Pages i-xvi

   PDF

2. Extended Abstracts

   1. Front Matter

      Pages 1-1

      PDF

   2. Computing the Rearrangement Distance of Natural Genomes

      • Leonard Bohnenkämper, Marília D. V. Braga, Daniel Doerr, Jens Stoye

      Pages 3-18

   3. Deep Large-Scale Multi-task Learning Network for Gene Expression Inference

      • Kamran Ghasedi Dizaji, Wei Chen, Heng Huang

      Pages 19-36

   4. A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Sets

      • Barış Ekim, Bonnie Berger, Yaron Orenstein

      Pages 37-53

   5. Multiple Competition-Based FDR Control and Its Application to Peptide Detection

      • Kristen Emery, Syamand Hasam, William Stafford Noble, Uri Keich

      Pages 54-71

   6. Supervised Adversarial Alignment of Single-Cell RNA-seq Data

      • Songwei Ge, Haohan Wang, Amir Alavi, Eric Xing, Ziv Bar-Joseph

      Pages 72-87

   7. Bagging MSA Learning: Enhancing Low-Quality PSSM with Deep Learning for Accurate Protein Structure Property Prediction

      • Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, Junzhou Huang

      Pages 88-103

   8. AStarix: Fast and Optimal Sequence-to-Graph Alignment

      • Pesho Ivanov, Benjamin Bichsel, Harun Mustafa, André Kahles, Gunnar Rätsch, Martin Vechev

      Pages 104-119Open Access

   9. Polynomial-Time Statistical Estimation of Species Trees Under Gene Duplication and Loss

      • Brandon Legried, Erin K. Molloy, Tandy Warnow, Sébastien Roch

      Pages 120-135

   10. RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin Occupancy

       • Sneha Mitra, Jianling Zhong, David M. MacAlpine, Alexander J. Hartemink

       Pages 136-151

   11. Representation of \(k\)-mer Sets Using Spectrum-Preserving String Sets

       • Amatur Rahman, Paul Medvedev

       Pages 152-168

   12. NetMix: A Network-Structured Mixture Model for Reduced-Bias Estimation of Altered Subnetworks

       • Matthew A. Reyna, Uthsav Chitra, Rebecca Elyanow, Benjamin J. Raphael

       Pages 169-185

   13. Stochastic Sampling of Structural Contexts Improves the Scalability and Accuracy of RNA 3D Module Identification

       • Roman Sarrazin-Gendron, Hua-Ting Yao, Vladimir Reinharz, Carlos G. Oliver, Yann Ponty, Jérôme Waldispühl

       Pages 186-201

   14. Lower Density Selection Schemes via Small Universal Hitting Sets with Short Remaining Path Length

       • Hongyu Zheng, Carl Kingsford, Guillaume Marçais

       Pages 202-217

3. Short Papers

   1. Front Matter

      Pages 219-219

      PDF

   2. Strain-Aware Assembly of Genomes from Mixed Samples Using Flow Variation Graphs

      • Jasmijn A. Baaijens, Leen Stougie, Alexander Schönhuth

      Pages 221-222

   3. Spectral Jaccard Similarity: A New Approach to Estimating Pairwise Sequence Alignments

      • Tavor Z. Baharav, Govinda M. Kamath, David N. Tse, Ilan Shomorony

      Pages 223-225

   4. MosaicFlye: Resolving Long Mosaic Repeats Using Long Reads

      • Anton Bankevich, Pavel Pevzner

      Pages 226-228

   5. Bayesian Non-parametric Clustering of Single-Cell Mutation Profiles

      • Nico Borgsmüller, Jose Bonet, Francesco Marass, Abel Gonzalez-Perez, Nuria Lopez-Bigas, Niko Beerenwinkel

      Pages 229-230

This book constitutes the proceedings of the 24^th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020, held in Padua, Italy, in May 2020. The 13 regular and 24 short papers presented were carefully reviewed and selected from 206 submissions. The papers report on original research in all areas of computational molecular biology and bioinformatics.

• communication channels (information theory)
• computer networks
• computer systems
• computer vision
• correlation analysis
• databases
• education
• engineering
• graph theory
• image processing
• internet
• learning
• machine learning
• mathematics
• network protocols
• optimization
• probability
• signal processing
• signal to noise ratio
• theoretical computer science

• Carnegie Mellon University, Pittsburgh, USA

  Russell Schwartz

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