RECOMB 2026 Accepted Papers

• Quartet-based species tree methods enable fast and consistent tree of blobs reconstruction under the network multispecies coalescent
  Junyan Dai, Yunheng Han and Erin Molloy

• Fast and Flexible Flow Decompositions in General Graphs via Dominators
  Francisco Sena and Alexandru I. Tomescu

• Predicting interaction-specific protein–protein interaction perturbations by missense variants with MutPred-PPI
  Ross Stewart, Florent Laval, Michael Calderwood, Matthew Mort, David Cooper, Marc Vidal and Predrag Radivojac

• KuPID: Kmer-based Upstream Preprocessing of Long Reads for Isoform Discovery
  Molly Borowiak and Yun William Yu

• Private Information Leakage from Polygenic Risk Scores
  Kirill Nikitin and Gamze Gursoy

• Privacy-Preserving Pangenome Graphs
  Jacob Blindenbach, Shaunak Soni and Gamze Gursoy

• ProtFlow: Flow Matching-based Protein Sequence Design with Comprehensive Protein Semantic Distribution Learning and High-quality Generation
  Zitai Kong, Yiheng Zhu, Yinlong Xu, Mingze Yin, Tingjun Hou, Jian Wu, Hongxia Xu and Chang-Yu Hsieh

• POTTR: Identifying Recurrent Trajectories in Evolutionary and Developmental Processes using Posets
  Sara C. Käufler, Henri Schmidt, Martin Jürgens, Gunnar W. Klau, Palash Sashittal and Benjamin J. Raphael

• SpecLig: Energy-Guided Hierarchical Model for Target-Specific 3D Ligand Design
  Peidong Zhang, Rong Han, Xiangzhe Kong, Ting Chen and Jianzhu Ma

• STELAR-X: Scaling Coalescent-Based Species Tree Inference to 100,000 Species and Beyond
  Anik Saha and Md Shamsuzzoha Bayzid

• A Cophylogenetic Approach for Virus-Host Interaction Prediction
  Md Zarzees Uddin Shah Chowdhury, T. M. Murali and Palash Sashittal

• Random Matrix Theory-guided sparse PCA for single-cell RNA-seq data
  Victor Chardès

• Prediction of lifetime disease liability from EHR features
  Yazheng Di and Na Cai

• Quantum and Temporal Graph Neural Networks Reveal New Accuracy Limits in Predicting Protein–Ligand Dissociation Kinetics
  Azamat Salamatov, Jun Bai, Gowtham Atluri and Chaowen Guan

• MaxGeomHash: An Algorithm for Variable-Size Random Sampling of Distinct Elements
  Mahmudur Rahman Hera, David Koslicki and Conrado Martínez

• Evolutionary dynamics under phenotypic uncertainty
  Vaibhav Mohanty, Anna Sappington, Eugene Shakhnovich and Bonnie Berger

• Deconvolving Phylogenetic Distance Mixtures
  Shayesteh Arasti, Ali Osman Berk Şapcı, Eleonora Rachtman, Mohammed El-Kebir and Siavash Mirarab

• Achieving spatial multi-omics integration from unaligned serial sections with DIME
  Pengyu Sun, Tian Mou, Xubin Zheng and Xinlei Huang

• Deep genomic models of allele-specific measurements
  Xinming Tu, Alexander Sasse, Kaitavjeet Chowdhary, Anna E. Spiro, Liang Yang, Maria Chikina, Christophe O. Benoist and Sara Mostafavi

• On Deriving Synteny Blocks by Compacting Elements
  Leonard Bohnenkämper, Luca Parmigiani, Cedric Chauve and Jens Stoye

• PaNDA: Efficient Optimization of Phylogenetic Diversity in Networks
  Niels Holtgrefe, Leo van Iersel, Ruben Meuwese, Yukihiro Murakami and Jannik Schestag

• Information Geometry Reconciles Discrete and Continuous Variation in Single-Cell and Spatial Transcriptomic Analysis
  Jinpu Cai, Yuxuan Wang, Yunhao Qiao, Cheng Wang, Ziqi Rong, Luting Zhou, Haoyang Liu, Meng Jiang, Hongbin Shen, Jingyi Jessica Li and Hongyi Xin

• Bacterial protein function prediction via multimodal deep learning
  Giulia Muzio, Michael Adamer, Leyden Fernandez, Lukas Miklautz, Karsten Borgwardt and Kemal Avican

• Alternet: Alternative splicing-aware gene regulatory network inference
  Juliane Hoffmann, Julia Wallnig, Ziheng Dai, Olga Tsoy, David B. Blumenthal and Anne Hartebrodt

• Bias in genome-wide association test statistics due to omitted interactions
  Burak Yelmen, Merve Nur Güler, Tõnu Kollo, Märt Möls, Guillaume Charpiat and Flora Jay

• Joint Learning of Drug-Drug Combination and Drug-Drug Interaction via Coupled Tensor-Tensor Factorization with Side Information
  Xiaoge Zhang, Zhengyu Fang, Kaiyu Tang, Huiyuan Chen and Jing Li

• Sequence-to-graph alignment based copy number calling using a network flow formulation
  Hugo Magalhães, Jonas Weber, Gunnar W. Klau, Tobias Marschall and Timofey Prodanov

• Fast, accurate construction of multiple sequence alignments from protein language embeddings
  Minh Hoang, Isabel Armour-Garb and Mona Singh

• SLAB: A Sweep Line Algorithm in PBWT for Finding Haplotype Block Cores
  Ardalan Naseri, Ahsan Sanaullah, Shaojie Zhang and Degui Zhi

• Compressed inverted indexes for scalable sequence similarity
  Florian Ingels, Lea Vandamme, Mathilde Girard, Clément Agret, Bastien Cazaux and Antoine Limasset

• Minimizer Density revisited: Models and Multiminimizers
  Florian Ingels, Lucas Robidou, Igor Martayan, Camille Marchet and Antoine Limasset

• DiCoLo: Integration-free and cluster-free detection of localized differential gene co-expression in single-cell data
  Ruiqi Li, Junchen Yang, Pei-Chun Su, Ariel Jaffe, Ofir Lindenbaum and Yuval Kluger

• bronko: ultrarapid, alignment-free detection of viral genome variation
  Ryan Doughty, Michael Tisza and Todd Treangen

• Arborist: Prioritizing Bulk DNA Inferred Tumor Phylogenies via Low-pass Single-cell DNA Sequencing Data
  Leah Weber, Chi Yin Ching, Chrisopher Ly, Yixiao Cheng, Chunxu Gao and Peter Van Loo

• Causal gene regulatory network inference from Perturb-seq via adaptive instrumental variable modeling
  Zhongxuan Sun, Hyunseung Kang and Sunduz Keles

• Summarizing RNA Structural Ensembles via Maximum Agreement Secondary Structures
  Xinyu Gu, Stefan Ivanovic, Daniel Feng and Mohammed El-Kebir

• CAMP: Coreset Accelerated Metacell Partitioning enables scalable analysis of single-cell data
  Danrong Li, Young Kun Ko and Stefan Canzar

• Multi-modal tissue-aware graph neural network for in silico genetic discovery
  Anusha Aggarwal, Ksenia Sokolova and Olga Troyanskaya

• CLADES — Contrastive Learning Augmented DifferEntial Splicing with Orthologous Positive Pairs
  Arghamitra Talukder, Nicholas Keung, Itsik Pe’Er and David A. Knowles

• MOSAIC: A Spectral Framework for Integrative Phenotypic Characterization Using Population-Level Single-Cell Multi-Omics
  Chang Lu, Yuval Kluger and Rong Ma

• GOPHER: Optimization-based Phenotype Randomization for Genome-Wide Association Studies with Differential Privacy
  Anupama Nandi, Seth Neel and Hyunghoon Cho

• Identifying Robust Subclonal Structures Through Tumor Progression Tree Alignment
  Chih Hao Wu, Jacob Gilbert, Salem Malikić and S. Cenk Sahinalp

• DeltaNMF: A Two-Stage Neural NMF for Differential Gene Program Discovery
  Anish Karpurapu, Charles Gersbach and Rohit Singh

• Transforming Biological Foundation Model Representations for Out-of-Distribution Data
  Aditya Pratapa, Rohit Singh and Purushothama Rao Tata

• A biobank-scale method for learning environmental modulators of gene–environment interaction underlying complex traits
  Zhengtong Liu, Arush Ramteke, Aakarsh Anand, Aditya Gorla, Moonseong Jeong and Sriram Sankararaman

• Integrative Inference of Spatially Informed Cell Lineage Trees using LineageMap
  Xinhai Pan, Yiru Chen and Xiuwei Zhang

• Uncertainty-aware synthetic lethality prediction with pretrained foundation models
  Kailey Hua, Ellie Haber and Jian Ma

• Evolutionary profile enhancement improves protein function annotation
  Shitong Dai, Jiaqi Luo and Yunan Luo

• Faster and Scalable Parallel External-Memory Construction of Colored Compacted de Bruijn Graphs with Cuttlefish 3
  Jamshed Khan, Laxman Dhulipala, Prashant Pandey and Rob Patro

• Nullstrap-DE: A General Framework for Calibrating FDR and Preserving Power in Differential Expression Methods, with Applications to DESeq2 and edgeR
  Chenxin Flora Jiang, Changhu Wang and Jingyi Jessica Li

• Gene-First Identity Construction for Robust Cell Identification in Single-Cell Transcriptomics
  Luqi Yang, Zhenwei Huang, Hongyi Xin and Jinpu Cai

• scDesignPop generates population-scale single-cell RNA-seq data for power analysis, method benchmarking, and privacy protection
  Chris Dong, Yihui Cen, Dongyuan Song and Jingyi Jessica Li

• Error Correction Algorithms for Efficient Gene Quantification in Single Cell Transcriptomics
  Jens Zentgraf, Johanna Schmitz, Andreas Keller and Sven Rahmann

• CycleGRN: Inferring Gene Regulatory Networks from Cyclic Flow Dynamics in Single-Cell RNA-seq Wenjun Zhao, Elana Fertig and Genevieve Stein-O’Brien

• Integrative Multi‑Scale Sequence–Structure Modeling for Antimicrobial Peptide Prediction and Design Jiayi Li, Yanruisheng Shao, Yu Li and Qinze Yu

• Modeling Multi-Modal Brain Connectomes for Brain Disorder Diagnosis via Graph Diffusion Optimal Transport Network Xiaoqi Sheng, Jiawen Liu, Jiaming Liang, Yiheng Zhang, Sankar Mondal, Yutong Li, Tinghe Zhang, Bing Liu, Jiangning Song and Hongmin Cai

• Fast and accurate resolution of ecDNA sequence using Cycle-Extractor Mahsa Faizrahnemoon, Jens Luebeck, King L. Hung, Suhas Rao, Matthew G. Jones, Paul S. Mischel, Howard Y. Chang, Kaiyuan Zhu and Vineet Bafna

• pHapCompass: Probabilistic Assembly and Uncertainty Quantification of Polyploid Haplotype Phase Marjan Hosseini, Ella Veiner, Thomas Bergendahl, Tala Yasenpoor, Zane Smith, Margaret Staton and Derek Aguiar

• Generating Hybrid Proteins with the MSA-Transformer Sanjana Tule, Samuel Davis, Ivan Koludarov, Ariane Mora and Mikael Boden

• scProfiterole: Clustering of Single-Cell Proteomic Data Using Graph Contrastive Learning via Spectral Filters Mustafa Coşkun, Filipa Blasco Lopes, Pınar Kubilay Tolunay, Mark R. Chance and Mehmet Koyutürk

• Constrained diffusion as a paradigm for evolution Daniel Lazarev, Anna Sappington, Grant Chau, Ruochi Zhang and Bonnie Berger

• Multimodal spatial alignment and morphology mapping with MOSAICField Xinhao Liu, Hongyu Zheng, Peter Halmos, Julian Gold, Erik Storrs, Li Ding and Ben Raphael

• Deconvolving mutation effects on protein stability and function with disentangled protein language models Kerr Ding, Ziang Li, Tony Tu, Jiaqi Luo and Yunan Luo

• Integrating morphology and gene expression in unpaired single-cell data using GeoAdvAE Jinqiu Du and Kevin Z. Lin

• Protein Compositional Ratio Representation (PCRR) Systematically Improves Human Disease Prediction Adithya Madduri, Randall Ellis and Chirag Patel