Program


Accepted Papers

  1. Fatemeh Almodaresi, Prashant Pandey, Michael Ferdman, Rob Johnson and Rob Patro.An Efficient and Scalable Representation of High-Dimensional Color Information Enabled via de Bruijn Graph Search
  2. Aryan Arbabi, David Adams, Sanja Fidler and Michael Brudno. Identifying clinical terms in free-text notes using ontology-guided machine learning
  3. Metin Balaban, Shahab Sarmashghi and Siavash Mirarab. APPLES: Fast Distance Based Phylogenetic Placement
  4. Bahar Behsaz, Hosein Mohimani, Alexey Gurevich, Andrey Prjibelski, Mark F Fisher, Larry Smarr, Pieter C. Dorrestein, Joshua S. Mylne and Pavel A. Pevzner. De Novo Peptide Sequencing Reveals a Vast Cyclopeptidome in Human Gut and Other Environments
  5. Philipp Benner and Martin Vingron. ModHMM: A modular supra-Bayesian genome segmentation method
  6. Lodewijk Brand, Liu Kai, Saad Elbeleidy, Hua Wang and Hao Zhang. Learning Robust Multi-Label Sample Specific Distances for Identifying HIV-1 Drug Resistance
  7. Dexiong Chen, Laurent Jacob and Julien Mairal. Biological Sequence Modeling with Convolutional Kernel Networks
  8. Van Hoan Do, Mislav Blažević, Pablo Monteagudo, Luka Borozan, Khaled Elbassioni, Soeren Laue, Francisca Rojas Ringeling, Domagoj Matijevic and Stefan Canzar. Dynamic pseudo-time warping of complex single-cell trajectories
  9. Rebecca Elyanow, Bianca Dumitrascu, Barbara E. Engelhardt, and Benjamin J. Raphael. netNMF: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data
  10. Boying Gong and Elizabeth Purdom. MethCP: Differentially Methylated Region Detection with Change Point Models
  11. Brian Hie, Hyunghoon Cho, Benjamin DeMeo, Bryan Bryson and Bonnie Berger. Geometric sketching of single-cell data preserves transcriptional structure
  12. Chirag Jain, Haowen Zhang, Yu Gao and Srinivas Aluru. On the Complexity of Sequence to Graph Alignment
  13. Jonathan Jou, Graham Holt, Anna Lowegard and Bruce Donald. Minimization-Aware Recursive K* (MARK*): A Novel, Provable Algorithm that Accelerates Ensemble-based Protein Design and Provably Approximates the Energy Landscape
  14. Mikhail Karasikov, Harun Mustafa, Amir Joudaki, Sara Javadzadeh No, Gunnar Rätsch and André Kahles. Sparse Binary Relation Representations for Genome Graph Annotation
  15. Younhun Kim, Frederic Koehler, Ankur Moitra, Elchanan Mossel and Govind Ramnarayan. How Many Subpopulations is Too Many? Exponential Lower Bounds for Inferring Population Histories
  16. Can Kockan, Kaiyuan Zhu, Natnatee Dokmai, Nikolai Karpov, Oguzhan Kulekci, David Woodruff and Cenk Sahinalp. Sketching Algorithms for Genomic Data Analysis and Querying in a Secure Enclave
  17. Alan Kuhnle, Taher Mun, Christina Boucher, Travis Gagie, Ben Langmead and Giovanni Manzini. Efficient Construction of a Complete Index for Pan-Genomics Read Alignment
  18. Haoyun Lei, Bochuan Lyu, E. Michael Gertz, Alejandro A. Schaffer, Xulian Shi, Kui Wu, Guibo Li, Liquin Xu, Yong Hu, Michael Dean and Russell Schwartz. Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data
  19. Yunan Luo, Jianzhu Ma, Xiaoming Zhao, Yufeng Su, Yang Liu, Trey Ideker and Jian Peng. Mitigating Data Scarcity in Protein Binding Prediction Using Meta-Learning
  20. Joel Mefford, Danny Park, Arthur Ko, Zhili Zheng, Markku Laakso, Paivi Pajukanta, Jian Yang, John Witte and Noah Zaitlen. Efficient estimation and applications of cross-validated genetic predictions
  21. Matthew Myers, Gryte Satas and Benjamin Raphael. Inferring tumor evolution from longitudinal samples
  22. Weihua Pan, Tao Jiang and Stefano Lonardi. OMGS: Optical Map-based Genome Scaffolding
  23. Ali Pazokitoroudi, Yue Wu, Kathryn S. Burch, Kangcheng Hou, Bogdan Pasaniuc and Sriram Sankararaman. Scalable multi-component linear mixed models with application to SNP heritability estimation
  24. Leonardo Pellegrina, Cinzia Pizzi and Fabio Vandin. Fast Approximation of Frequent k-mers and Applications to Metagenomics
  25. Kristoffer Sahlin and Paul Medvedev. De novo clustering of long-read transcriptome data using a greedy, quality-value based algorithm
  26. Shahab Sarmashghi and Vineet Bafna. A Note on Computing Interval Overlap Statistics
  27. Itay Sason, Damian Wojtowicz, Welles Robinson, Mark Leiserson, Teresa Przytycka and Roded Sharan. A sticky multinomial mixture model of strand-coordinated mutational processes in cancer
  28. Mike Thompson, Zeyuan Johnson Chen, Elior Rahmani and Eran Halperin. Recovery of cell-type composition in methylation data using canonical correlation analysis
  29. Sheng Wang, Emily Flynn and Russ Altman. GRep: Gene Set Representation via Gaussian Embedding
  30. Yijie Wang, Jan Hoinka and Teresa M. Przytycka. Accurate sub-population detection and mapping across single cell experiments with PopCorn
  31. Ziheng Wang, Grace Ht Yeo, Richard Sherwood and David Gifford. Disentangled Representations of Cellular Identity
  32. Ye Wu, Ruibang Luo, Henry C.M. Leung, Hing-Fung Ting and Tak-Wah Lam. RENET: A Deep Learning Approach for Extracting Gene-Disease Associations from Literature
  33. Yue Wu, Anna Yaschenko, Mohammadreza Hajy Heydary, and Sriram Sankararaman. Fast estimation of genetic correlation for Biobank-scale data
  34. Jinbo Xu. Distance-based Protein Folding Powered by Deep Learning
  35. Yang Yang, Yang Zhang, Bing Ren, Jesse Dixon and Jian Ma. Comparing 3D Genome Organization in Multiple Species using Phylo-HMRF
  36. Jesse Zhang, Govinda Kamath and David Tse. Towards a post-clustering test for differential expression
  37. Martin Zhang, Fei Xia and James Zou. AdaFDR: a Fast, Powerful and Covariate-Adaptive Approach for Multiple Hypothesis Testing