RECOMB 2022

The 26th Annual International Conference on Research in Computational Molecular Biology
La Jolla, USA, May 22-25, 2022

Accepted Papers

  • Max Hill and Sebastien Roch. On the Effect of Intralocus Recombination on Triplet-Based Species Tree Estimation
  • Kun Qian, Shiwei Fu, Hongwei Li and Wei Vivian Li. A novel matrix factorization model for interpreting single-cell gene expression from biologically heterogeneous data
  • Michael Ford, Ananth Hari, Oscar Rodriguez, Junyan Xu, Justin Lack, Cihan Oguz, Yu Zhang, Sarah Weber, Mary Magliocco, Jason Barnett, Sandhya Xirasagar, Smilee Samuel, Luisa Imberti, Paolo Bonfanti, Andrea Biondi, Clifton Dalgard, Stephen Chanock, Lindsey Rosen, Steven Holland, Helen Su, Luigi Notarangelo, Uzi Vishkin, Corey Watson and S. Cenk Sahinalp. ImmunoTyper-SR: A Novel Computational Approach for Genotyping Immunoglobulin Heavy Chain Variable Genes using Short Read Data
  • Elior Rahmani, Michael Jordan and Nir Yosef. Identifying systematic variation at the single-cell level by leveraging low-resolution population-level data
  • Amatur Rahman and Paul Medvedev. Uncovering hidden assembly artifacts: when unitigs are not safe and bidirected graphs are not helpful
  • Ruochi Zhang, Tianming Zhou and Jian Ma. Ultrafast and Interpretable Single-cell 3D Genome Analysis with Fast-Higashi
  • Chuanyi Zhang, Palash Sashittal and Mohammed El-Kebir. CORSID enables de novo identification of transcription regulatory sequences and genes in coronaviruses
  • Dongshunyi Li, Jun Ding and Ziv Bar-Joseph. Unsupervised cell functional annotation for single-cell RNA-Seq
  • Pedro F. Ferreira, Jack Kuipers and Niko Beerenwinkel. Mapping single-cell transcriptomes to copy number evolutionary trees
  • Xiang Ge Luo, Jack Kuipers and Niko Beerenwinkel. Joint inference of repeated evolutionary trajectories and patterns of clonal exclusivity or co-occurrence from tumor mutation trees
  • Pesho Ivanov, Benjamin Bichsel and Martin Vechev. Fast and Optimal Sequence-to-Graph Alignment Guided by Seeds
  • Haohan Wang, Oscar Lopez, Wei Wu and Eric Xing. Transcriptome Association Study Guided by Gene Regulatory Network
  • Uthsav Chitra, Tae Yoon Park and Ben Raphael. NetMix2: Unifying network propagation and altered subnetworks
  • Pinar Demetci, Rebecca Santorella, Bjorn Sandstede and Ritambhara Singh. Unsupervised integration of single-cell multi-omics datasets with disparities in cell-type representation
  • Yang Yang, Yuchuan Wang, Yang Zhang and Jian Ma. CONCERT: Genome-wide prediction of sequence elements that modulate DNA replication timing
  • Pengfei Zhang, Zhengyuan Jiang, Yixuan Wang and Yu Li. CLMB: deep contrastive learning for robust metagenomic binning
  • Quang Minh Hoang, Hongyu Zheng and Carl Kingsford. DeepMinimizer: A Differentiable Framework for Optimizing Sequence-Specific Minimizer Schemes
  • Vijini Mallawaarachchi and Yu Lin. MetaCoAG: Binning Metagenomic Contigs via Composition, Coverage and Assembly Graphs
  • Seyran Saeedi, Myrna Serrano, Dennis Yang, Paul Brooks, Gregory Buck and Tom Arodz. Real-valued Group Testing for Quantitative Molecular Assays
  • Eleonora Rachtman, Shahab Sarmashghi, Vineet Bafna and Siavash Mirarab. Uncertainty quantification using subsampling for assembly-free estimates of genomic distance and phylogenetic relationships
  • Chirag Jain, Daniel Gibney and Sharma V. Thankachan. Co-linear chaining with overlaps and gap costs
  • Sazan Mahbub, Shashata Sawmya, Arpita Saha, Rezwana Reaz, M. Sohel Rahman and Md. Shamsuzzoha Bayzid. QT-GILD: Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data
  • Dunming Hua, Ming Gu, Yanyi Du, Li Qi, Xiangjun Du, Zhidong Bai, Xiaopeng Zhu and Dechao Tian. DiffDomain enables identification of structurally reorganized topologically associating domains
  • Hanwen Xu and Sheng Wang. ProTranslator: zero-shot protein function prediction using textual description
  • Daniel Gibney, Sharma V. Thankachan and Srinivas Aluru. The Complexity of Approximate Pattern Matching on De Bruijn Graphs
  • Pavel Skums, Fatemeh Mohebbi, Viachaslau Tsyvina, Pelin Burcak Icer and Yury Khudyakov. SOPHIE: viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework
  • Nathan Guerin, Teresa Kaserer and Bruce Donald. Resistor: an algorithm for predicting resistance mutations using Pareto optimization over multistate protein design and mutational signatures
  • Mikhail Karasikov, Harun Mustafa, Gunnar Ratsch and Andre Kahles. Lossless Indexing with Counting de Bruijn Graphs
  • Alireza Ganjdanesh, Jipeng Zhang, Wei Chen and Heng Huang. From Multi-Modal Genotype and Phenotype Mutual Learning to Single-Modal Input for Longitudinal Outcome Prediction
  • Joshua Wetzel, Kaiqian Zhang and Mona Singh. Learning probabilistic protein-DNA recognition codes from DNA-binding specificities using structural mappings
  • Fernando H. C. Dias, Lucia Williams, Brendan Mumey and Alexandru I. Tomescu. Fast, Flexible, and Exact Minimum Flow Decompositions via ILP
  • Shahbaz Khan, Milla Kortelainen, Manuel Caceres, Lucia Williams and Alexandru I. Tomescu. Safe and Complete Flow Decompositions for RNA Assembly
  • Meihua Dang, Anji Liu, Xinzhu Wei, Sriram Sankararaman and Guy Van den Broeck. Tractable and expressive generative models of genetic variation data
  • Cong Ma, Uthsav Chitra, Shirley Zhang and Benjamin Raphael. Belayer: Modeling distinct cell type clusters and continuous variation of expression in spatial transcriptomics from layered tissues
  • Agniva Chowdhury, Aritra Bose, Samson Zhou, David P. Woodruff and Petros Drineas. A Fast, Provably Accurate Approximation Algorithm for Sparse Principal Component Analysis Reveals Human Genetic Variation Across the World
  • Chen Li, Maria Virgilio, Kathleen Collins and Joshua Welch. Single-cell multi-omic velocity infers dynamic and decoupled gene regulation
  • Ran Zhang, William Noble, Laetitia Meng-Papaxanthos and Jean-Philippe Vert. Semi-supervised single-cell cross-modality translation using Polarbear
  • Jingkang Zhao, Vincentius Martin and Raluca Gordan. Transcription Factor-Centric Approach to Identify Non-Recurring Putative Regulatory Drivers in Cancer
  • Ulzee An, Na Cai, Andy Dahl and Sriram Sankararaman. AutoComplete: Deep Learning-based Phenotype Imputation for Large-scale Biomedical Data
  • Zheng Dai, Sachit Saksena, Geraldine Horny, Christine Banholzer, Stefan Ewert and David Gifford. Ultra high diversity factorizable libraries for efficient therapeutic discovery

RECOMB 2022, LA JOLLA, CA, USA, MAY 22-25, 2022

Email: recomb2022@ucsd.edu

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