Genomics

Follow this topic Ask about this topic

Momentum

7 papers in the last four weeks, up 40% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 79

All topics

$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps
May 20, 2026Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel +2Genomics Inverse Problems
Univ. Grenoble Alpes, Inria CNRS, Grenoble INP, LJK, France · TIMC, Univ. Grenoble Alpes CNRS, Grenoble INP, France
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
May 18, 2026Qi Si, Penglei Wang, Yushuai Wu +5Spatial Transcriptomics Spatial Gene Expression Prediction
Shanghai Academy of Artificial Intelligence for Science, Shanghai, China. · School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. · Artificial Intelligence Innovation and Incubation Institute, Fudan University, Shanghai, China.
AttnGen: Attention-Guided Saliency Learning for Interpretable Genomic Sequence Classification
May 13, 2026Rayhaneh Shabani Nia, Ali KarkehabadiNeural Network Interpretability Attention Mechanisms
University of California, Davis California, USA
Set-Aggregated Genome Embeddings for Microbiome Abundance Prediction
May 12, 2026Younhun Kim, Georg K. Gerber, Travis E. GibsonRepresentation Learning Genomics
1Brigham and Women’s Hospital, Boston, MA, USA · 2Harvard Medical School, Boston, MA, USA
RNA-FM: Flow-Matching Generative Model for Genome-wide RNA-Seq Prediction
May 12, 2026Yaxuan Song, Jianan Fan, Tianyi Wang +4Computational Pathology Genomics
School of Computer Science, The University of Sydney, Australia · Biological Systems and Engineering Division, Lawrence Berkeley National Lab, USA · Berkeley Biomedical Data Science Center, Lawrence Berkeley National Lab, USA +1
LPDP: Inference-Time Reward Control for Variable-Length DNA Generation with Edit Flows
May 12, 2026Jeongchan Kim, Yunkyung Ko, Jong Chul YeInference-Time Search Generative Modeling
KAIST AI
SCOPE: Siamese Contrastive Operon Pair Embeddings for Functional Sequence Representation and Classification
May 10, 2026Akarsh Gupta, Kenneth Rodrigues, Sagnik ChatterjeeGenomics Molecular Representation Learning
MicroFuse: Protein-to-Genome Expert Fusion for Microbial Operon Reasoning
May 9, 2026Seungik ChoGenomics Multimodal Fusion
Department of Physics and Astronomy, Rice University, Texas, USA.
Wisteria: A Unified Multi-Scale Feature Learning Framework for DNA Language Model
May 7, 2026Weihua Wang, Haoji Li, Feilong Bao +2Representation Learning Language Modeling
College of Computer Science, Inner Mongolia University, Hohhot, Inner Mongolia, 010021, China · National and Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian, Hohhot, Inner Mongolia, 010021, China · Inner Mongolia Key Laboratory of Multilingual Artificial Intelligence Technology, Hohhot, Inner Mongolia, 010021, China +1
When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data
May 6, 2026Miguel Fernandez-de-Retana, Ruben Sanchez-Corcuera, Unai Zulaika +2Causal Discovery Gene Regulatory Network Inference
Faculty of Engineering University of Deusto Bilbao, Spain
EFGPP: Exploratory framework for genotype-phenotype prediction
May 2, 2026Muhammad Muneeb, David B. AscherGenomics Multimodal Fusion
School of Chemistry and Molecular Biology, The University of Queensland, Brisbane, 4067, Australia · Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, 3004, Australia
CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation
Apr 30, 2026Andac Demir, Erik W. Anderson, Jeremy L. Jenkins +1Single-Cell Perturbation Modeling Genomics
Novartis Biomedical Research
Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification
Apr 28, 2026Wenxi Zhu, Wensheng Gan, Zhenlian QiGenomics Sequence Modeling
College of Information Science and Technology, Jinan University, Guangzhou 510632, China · College of Cyber Security, Jinan University, Guangzhou 510632, China · Guangdong Eco-Engineering Polytechnic, Guangzhou 510520, China
MIMIC: A Generative Multimodal Foundation Model for Biomolecules
Apr 27, 2026Siavash Golkar, Jake Kovalic, Irina Espejo Morales +28Molecular Generation Genomics
Polymathic AI · Center for Data Science, New York University · Department of Applied Physics, Yale University +17
StackFeat RL: Reinforcement Learning over Iterative Dual Criterion Feature Selection for Stable Biomarker Discovery
Apr 24, 2026A. Yermekov, D. A. Herrera-MartíScientific Discovery Feature Selection
PAfoS.AI, Almaty, Kazakhstan · CEA List, Université Grenoble Alpes, France
Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2
Apr 23, 2026Isabel Kurth, Paulo Yanez Sarmiento, Bernhard Y. RenardTransformer Interpretability Attention Mechanisms
Hasso Plattner Institute University of Potsdam
Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions
Mar 2, 2026Amir Asiaee, Kavey Aryan, James P. LongSelective Inference Causal Structure Learning
Department of Biostatistics, Vanderbilt University Medical Center, TN 37203, USA · Department of Informatics, King’s College London, London, UK · Department of Biostatistics, MD Anderson Cancer Center, Houston, TX, USA
Central Dogma Transformer II: An AI Microscope for Understanding Cellular Regulatory Mechanisms
Feb 9, 2026Nobuyuki OtaTransformer Interpretability Single-Cell Perturbation Modeling
Independent Researcher, Burlingame, CA, USA
Leveraging Natural Language Processing to Unravel the Mystery of Life: A Review of NLP Approaches in Genomics, Transcriptomics, and Proteomics
Jun 2, 2025Ella Rannon, David BursteinProtein Language Models Genomics
The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv, Israel

May 20, 2026, cs.LGJ/K move · Enter open · S save

$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps

Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel, Nelle Varoquaux+1

Univ. Grenoble Alpes, Inria CNRS, Grenoble INP, LJK, France · TIMC, Univ. Grenoble Alpes CNRS, Grenoble INP, France

Genomics Inverse Problems

Open paper AskPDF arXiv

Locating genomic features from genomic contact maps, such as centromere identification from genome-wide chromosome conformation capture techniques, notably Hi-C, can be formulated as an inverse problem: infer one parameter per entity given a map summarizing pairwise interactions through blocks of variable numbers and sizes. In this work, we introduce a data-driven approach that leverages shared structure between these contact maps, such as global alignment between localized patterns, while handling the variability in number and size of chromosomes arising in real-world data. Our approach relies on a transformer architecture capable of handling such variability and a custom simulator to generate abundant, yet computationally cheap synthetic data for training. Applied to the problem of centromere localization, the method recovers genomic positions at or below the map resolution across species with various genome sizes using a coarse-to-fine refinement step when chromosome sizes fall outside the training range. We concentrate our evaluation on Hi-C data, where the block structure is well characterized and ground truth is available.

Momentum

Related topics

Latest papers 79