August 29 - September 1, 2021


Accepted Papers for RECOMB 2021 Proceedings

1. Carlos Oliver, Vincent Mallet, Pericles Philippopoulos, William L. Hamilton and Jerome Waldispuhl.

VeRNAl: Mining RNA Structures for Fuzzy Base Pairing Network Motifs


2. Jim Shaw and Yun William Yu.

Practical probabilistic and graphical formulations of long-read polyploid haplotype phasing


3. Martin Grosshauser, Paul Zaharias and Tandy Warnow.

Re-evaluating deep neural networks for phylogeny estimation: the issue of taxon sampling


4. Enrico Seiler, Svenja Mehringer, Mitra Darvish, Etienne Turc and Knut Reinert.

Raptor: A fast and space-efficient pre-filter for querying very large collections of nucleotide sequences


5. Kaiyuan Zhu, Welles Robinson, Alejandro Schaffer, Junyan Xu, Eytan Ruppin, Funda Ergun, Yuzhen Ye and S. Cenk Sahinalp.

Strain Level Microbial Detection and Quantification with Applications to Single Cell Metagenomics


6. Rami Nasser, Yonina Eldar and Roded Sharan.

Deep unfolding for non-negative matrix factorization with application to mutational signature analysis


7. Hongyu Zheng, Cong Ma and Carl Kingsford.

Deriving Ranges of Optimal Estimated Transcript Expression due to Non-identifiability


8. Yoshihiro Shibuya and Gregory Kucherov.

Set-Min sketch: a probabilistic map for power-law distributions with application to k-mer annotation


9. Samuel Sledzieski, Rohit Singh, Lenore Cowen and Bonnie Berger.

Sequence-based prediction of protein-protein interactions: a structure-aware interpretable deep learning model


10. Nicholas Franzese, Jason Fan, Roded Sharan and Mark D.M. Leiserson.

ScalpelSig: Automated Design of Genomic Panels to Expand Clinical Access to Mutational Signature Analysis


11. Yueyu Jiang, Metin Balaban and Siavash Mirarab.

DEPP: Deep Learning Enables Extending Species Trees using Single Genes


12. Xinhao Liu, Huw A. Ogilvie and Luay Nakhleh.

Variational Inference Using Approximate Likelihood Under the Coalescent With Recombination


13. Tianyi Sun, Dongyuan Song, Wei Vivian Li and Jingyi Jessica Li.

scDesign2: an interpretable simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured


14. Siavash Raeisi Dehkordi, Jens Luebeck and Vineet Bafna.

FaNDOM: Fast Nested Distance-based seeding of Optical Maps


15. Yuxuan Du, Sarah Laperriere, Jed Fuhrman and Fengzhu Sun.

HiCzin: Normalizing metagenomic Hi-C data and detecting spurious contacts using zero-inflated negative binomial regression


16. Harsh Shrivastava, Xiuwei Zhang, Le Song and Srinivas Aluru.

An Unrolled Deep Learning Framework for Single Cell Gene Regulatory Networks


17. Anton Bankevich, Andrey Bzikadze, Mikhail Kolmogorov and Pavel Pevzner.

Assembling Long Accurate Reads Using de Bruijn Graphs


18. Ali Pazokitoroudi, Andy Dahl, Noah Zaitlen, Saharon Rosset and Sriram Sankararaman.

Biobank-scale estimation of the proportion of trait variance explained by gene-environment interactions


19. Jin Li and Jinbo Xu.

Study of Real-Valued Distance Prediction For Protein Structure Prediction with Deep Learning


20. Barış Ekim, Bonnie Berger and Rayan Chikhi.

Minimizer-space de Bruijn Graphs


21. Han Li, Xinyi Zhao, Shuya Li, Fangping Wan, Jianyang Zeng and Dan Zhao.

MoTSE: an interpretable task similarity estimator for small molecular property prediction tasks


22. Diego Santoro, Leonardo Pellegrina and Fabio Vandin.

SPRISS: Approximating Frequent k-mers by Sampling Reads, and Applications


23. Damian Wójtowicz, Jan Hoinka, Bayarbaatar Amgalan, Yoo-Ah Kim and Teresa M. Przytycka.

RepairSig: Deconvolution of DNA damage and repair contributions to the mutational landscape of cancer


24. Amir Joudaki, Gunnar Ratsch and Andre Kahles.

Fast Alignment-Free Similarity Estimation By TensorSketching


25. Xiang Zhou, Hua Chai, Yuansong Zeng, Huiying Zhao, Ching-Hsing Luo and Yuedong Yang.

scAdapt: Virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species


26. Shahab Sarmashghi, Metin Balaban, Eleonora Rachtman, Behrouz Touri, Siavash Mirarab and Vineet Bafna.

Estimating repeat spectra and genome length from low-coverage genome skims with RESPECT


27. Benjamin Chidester, Tianming Zhou and Jian Ma.

SPICEMIX: Integrative single-cell spatial modeling for inferring cell identity


28. Antonio Blanca, Robert Harris, David Koslicki and Paul Medvedev.

The statistics of k-mers from a sequence undergoing a simple mutation process without spurious matches


29. Hua-Ting Yao, Jerome Waldispuhl, Yann Ponty and Sebastian Will.

Taming Disruptive Base Pairs to Reconcile Positive and Negative Structural Design of RNA


30. Ruochi Zhang, Jianzhu Ma and Jian Ma.

Towards the prediction of higher-order genetic interactions


31. Massimiliano Rossi, Marco Oliva, Ben Langmead, Travis Gagie and Christina Boucher.

MONI: A Pangenomics Index for Finding MEMs


32. Natnatee Dokmai, Can Kockan, Kaiyuan Zhu, Xiaofeng Wang, S. Cenk Sahinalp and Hyunghoon Cho.

Privacy-Preserving Genotype Imputation in a Trusted Execution Environment


33. Pinar Demetci, Rebecca Santorella, Bjorn Sandstede, William Stafford Noble and Ritambhara Singh. 

Gromov-Wasserstein optimal transport to align single-cell multi-omics data


34. Baraa Orabi, Brian McConeghy, Cedric Chauve and Faraz Hach.

Freddie: Annotation-independent Detection and Discovery of Transcriptomic Alternative Splicing Isoforms


35. Lupeng Kong, Fusong Ju, Wei-Mou Zheng, Siwei Sun, Jinbo Xu and Dongbo Bu.

ProALIGN: directly learning alignments for protein structure prediction via exploiting context-specific alignment motifs


36. Gryte Satas, Simone Zaccaria, Mohammed El-Kebir and Benjamin J Raphael.

DeCiFering the Elusive Cancer Cell Fraction in Tumor Heterogeneity and Evolution


37. Yuepeng Jiang, Stefano Rensi, Sheng Wang and Russ Altman.

DrugOrchestra: Jointly predicting drug response, targets, and side effects via deep multi-task learning


38. Ron Zeira, Max Land and Ben Raphael.

Alignment and Integration of Spatial Transcriptomics Data

39. Wei Vivian Li and Yanzeng Li.

scLink: Inferring Sparse Gene Co-expression Networks from Single-cell Expression Data


40. Serhan Yılmaz, Marzieh Ayati, Daniela Schlatzer, A. Ercument Cicek, Mark Chance and Mehmet Koyuturk.

Robust Inference of Kinase Activity Using Functional Networks

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