June 22 - 25, 2020



RECOMB 2020 will be a virtual conference

to be held on June 22-25, 2020.

Register here!


1. Jasmijn Baaijens, Leen Stougie and Alexander Schoenhuth.
   Strain-aware assembly of genomes from mixed samples using flow variation graphs

2. Tavor Baharav, Govinda Kamath, David Tse and Ilan Shomorony.
     Spectral Jaccard Similarity: A new approach to estimating pairwise sequence alignments

3. Anton Bankevich and Pavel Pevzner.
    mosaicFlye: resolving mosaic segmental duplication using long error-prone reads

4. Leonard Bohnenkämper, Marilia Braga, Daniel Doerr and Jens Stoye.
    Computing the rearrangement distance of natural genomes

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

    Bayesian non-parametric clustering of single-cell mutation profiles

6. Jannis Born, Matteo Manica, Ali Oskooei, Joris Cadow and María Rodríguez Martínez.
     PaccMann RL : Designing anticancer drugs from transcriptomic data via reinforcement learning

7. Aritra Bose, Myson Burch, Agniva Chowdhury, Peristera Paschou and Petros Drineas.
    CluStrat: a structure informed clustering strategy for population stratification

8. Nadav Brandes, Nathan Linial and Michal Linial.
    PWAS: Proteome-Wide Association Study

9. Christa Caggiano, Barbara Celona, Fleur Garton, Joel Mefford, Brian Black, Naomi Wray, Catherine Lomen-Hoerth, Andrew Dahl and Noah  Zaitlen.
    Estimating the rate of cell type degeneration from epigenetic sequencing of cell-free DNA


10. Gizem Caylak and A. Ercument Cicek.
      Potpourri: An Epistasis Test Prioritization Algorithm via Diverse SNP Selection

11. Hyunghoon Cho, Sean Simmons, Ryan Kim and Bonnie Berger.
  Privacy-preserving biomedical database queries with optimal privacy-utility trade-offs


12. Kamran Ghasedi Dizaji and Heng Huang.
      Deep Large-Scale Multi-Task Learning Network for Gene Expression Inference

13. Baris Ekim, Bonnie Berger and Yaron Orenstein.
     A randomized parallel algorithm for efficiently finding near-optimal universal hitting sets

14. Kristen Emery, Syamand Hasam, William Stafford Noble and Uri Keich.

      Multiple competition-based FDR control and its application to peptide detection


15. Chao Gao and Joshua Welch.
      Iterative Refinement of Cellular Identity from Single-Cell Data Using Online Learning


16. Songwei Ge, Haohan Wang, Amir Alavi, Eric P. Xing and Ziv Bar-Joseph.
      Supervised Adversarial Alignment of Single-Cell RNA-seq Data


17. Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang and Junzhou Huang.
     Bagging MSA Learning: Enhancing Low-quality PSSM with Deep Learning for Accurate Protein Structure Property Prediction


18. Borislav Hristov, Bernard Chazelle and Mona Singh.
   A guided network propagation approach to identify disease genes that combines prior and new information


19. Pesho Ivanov, Benjamin Bichsel, Harun Mustafa, André Kahles, Gunnar Rätsch, Martin Vechev.
      AStarix: Fast and Optimal Sequence-to-Graph Alignment


20. Ruth Johnson, Kathryn S. Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc and Sriram Sankararaman.
      A scalable method for estimating the regional polygenicity of complex traits


21. Tyler Joseph, Amey Pasarkar and Itsik Pe'Er.
      Efficient and accurate inference of microbial trajectories from longitudinal count data


22. Nathan Lapierre, Kodi Taraszka, Rosemary He, Helen Huang, Farhad Hormozdiari and Eleazar Eskin.
      Identifying Causal Variants by Fine Mapping Across Multiple Studies


23. Brandon Legried, Erin Molloy, Tandy Warnow and Sebastien Roch.
       Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss


24.  Shuya Li, Fangping Wan, Hantao Shu, Tao Jiang, Dan Zhao and Jianyang Zeng.
       MONN: a Multi-Objective Neural Network for Predicting Pairwise Non-Covalent Interactions and Binding Affinities between Compounds and  Proteins


25. Yunan Luo, Lam Vo, Hantian Ding, Yufeng Su, Yang Liu, Wesley Wei Qian,
       Huimin Zhao and Jian Peng. Evolutionary context-integrated deep sequence modeling for protein engineering

26. Uyen Mai and Siavash Mirarab.
       Log Transformation Improves Dating of Phylogenies


27. Sneha Mitra, Jianling Zhong, David MacAlpine and Alexander Hartemink.
      RoboCOP: Multivariate state space model integrating epigenomic accessibility data to elucidate genome-wide chromatin occupancy


28. Brooks Paige, James Bell, Aurélien Bellet, Adrià Gascón and Daphne Ezer.
       Reconstructing genotypes in private genomic databases from genetic risk scores


29. Amatur Rahman and Paul Medvedev.
       Representation of k-mer sets using spectrum-preserving string sets


30. Matthew Reyna, Uthsav Chitra, Rebecca Elyanow and Benjamin Raphael.
       NetMix: A network-structured mixture model for reducing bias in the identification of altered subnetworks


31. Ahsan Sanaullah, Degui Zhi and Shaojie Zhang.
     d-PBWT: dynamic positional Burrows-Wheeler transform


32. Roman Sarrazin-Gendron, Hua-Ting Yao, Vladimir Reinharz, Carlos G. Oliver, Yann Ponty and Jérôme Waldispühl.
       Stochastic Sampling of Structural Contexts Improves the Scalability and Accuracy of RNA 3D Modules Identification


33. Itay Sason, Yuexi Chen, Max Leiserson and Roded Sharan.
      A mixture model for signature discovery from sparse mutation data


34. Gryte Satas, Simone Zaccaria, Geoffrey Mon and Benjamin J. Raphael.
      Single-cell tumor phylogeny inference with copy-number constrained mutation losses


35. Yijie Wang, Justin Fear, Isabelle Berger, Hangnoh Lee, Brian Oliver and Teresa Przytycka.
       Reconstruction of Gene Regulatory Networks by integrating biological model and a recommendation system


36. Ruochi Zhang and Jian Ma.
       Probing multi-way chromatin interaction with hypergraph representation learning


37. Hongyu Zheng, Carl Kingsford and Guillaume Marçais.
      Lower density selection schemes via small universal hitting sets with short remaining path length