ICML 2025PastGenerative models
ICML 2025 Generative AI and Biology (GenBio) Workshop
GenBio 2025
- Submission deadline
- May 26, 2025, 11:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (145)
Fetched from OpenReview (v2) on 2026-06-10.
A Diffusion Model to Shrink Proteins While Maintaining their Function
A Diffusion-Based Autoencoder for Learning Patient-Level Representations from Single-Cell Data
A framework to extract and interpret biological concepts from scRNAseq generative foundation models
A Genomic Language Model for Zero-Shot Prediction of Promoter Indel Effects
A Ground-Up Designed Controllable GPT for Molecule Optimization
A Zero-shot LLM-based Framework for Descriptive Gene-gene Interaction Network Generation
AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion
Active Leaning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generation
Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics
Amortized Sampling with Transferable Normalizing Flows
An Improved Systematic Method for Constructing Enzyme-Constrained Genome-Scale Metabolic Models Using a Protein-Chemical Transformer
An Iterative Framework for Generative Backmapping of Coarse Grained Proteins
Analytic Gaussian Convolution for Faster Molecular Optimization and Sampling
AntiDIF: Accurate and Diverse Antibody Specific Inverse Folding with Discrete Diffusion
AtoMAE: Learning Protein Structure Representations from Atomic Voxel Grids via Masked Autoencoders
ATOMICA: Learning Universal Representations of Molecular Interactions
Automated Neuron Labelling Enables Generative Steering and Interpretability in Protein Language Models
Balancing Speed and Precision in Protein Folding: A Comparison of AlphaFold2, ESMFold, and OmegaFold
BC-Design: A Biochemistry-Aware Framework for Highly Accurate Inverse Protein Folding
Benchmark of Diffusion and Flow Matching Models for Unconditional Protein Structure Design
Beyond Visual Inspection: Principled Benchmarking of Single-Cell Trajectory Representations with scTRAM
Bimodal masked language modeling for bulk RNA-seq and DNA methylation representation learning
BindEnergyCraft: Casting Protein Structure Predictors as Energy-Based Models for Binder Design
Biological Reasoning with Reinforcement Learning through Natural Language Enables Generalizable Zero-Shot Cell Type Annotations
BoltzNCE: Learning Likelihoods for Boltzmann Generation with Stochastic Interpolants and Noise Contrastive Estimation
Bridging Quantum and Classical Computing in Drug Design: Architecture Principles for Improved Molecule Generation
Bures-Wasserstein Flow Matching for Graph Generation
Calibrating Generative Models
Chemical Reaction Network Implementation of Logic Gates and Neural Networks Using a Molecular Exchange Mechanism
CoFM: Molecular Conformation Generation via Flow Matching in SE(3)-Invariant Latent Space
Connecting Gene Expression and Tissue Morphology with Conditional Generative Models
Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models
Constrained Molecular Generation via Sequential Flow Model Fine-Tuning
CryoSAMU: Enhancing 3D Cryo-EM Density Maps of Protein Structures at Intermediate Resolution with Structure-Aware Multimodal U-Nets
DePO: Elicit Chemical Reasoning Capability via Demonstration-Guided Policy Optimization
Design in Voxel Space Decode in SMILES Space: Plixer Generates Drug-Like Molecules for Protein Pockets
Diffusion models with group symmetries for biomolecule generation
Diffusion-Free Graph Generation with Next-Scale Prediction
DisProtEdit: Exploring Disentangled Representations for Multi-Attribute Protein Editing
DIVER-0 : A Fully Channel Equivariant EEG Foundation Model
Diversity by Design: Addressing Mode Collapse Improves scRNA-seq Perturbation Modeling on Well-Calibrated Metrics
Do we need equivariant models for molecule generation?
Drug Discovery SMILES-to-Pharmacokinetics Diffusion Models with Deep Molecular Understanding
eccDNAMamba: A Pre-Trained Model for Ultra-Long eccDNA Sequence Analysis
Efficient Models For Molecular Property Prediction
Electrostatics from Laplacian Eigenbasis for Neural Network Interatomic Potentials
Enhancing AlphaFold3 for Protein-Ligand Co-Folding via Reinforcement Learning
EpiBinder: a multimodal deep learning model at base-resolution to analyze in vivo Transcription Factor-DNA Binding
EpitopeGen: Learning to Generate T Cell Epitopes: A Semi-Supervised Approach with Biological Constraints
Exploring Adversarial Robustness in Classification tasks using DNA Language Models
Fast and Scalable Gene Embedding Search: A Comparative Study of FAISS and ScaNN
FIGRDock: Fast Interaction-Guided Regression for Flexible Docking
Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning
Forecasting H1N1 Influenza Pandemic and Seasonal Evolution
Foreground-aware Virtual Staining for Accurate 3D Cell Morphological Profiling
FORT: Forward-Only Regression Training of Normalizing Flows
From Fragments to Geometry: A Unified Graph Transformer for Molecular Representation from Conformer Ensembles
Generating readily synthesizable dye scaffolds with SyntheFluor
Generation of structure-guided pMHC-I libraries using Diffusion Models
Guided Generation for Developable Antibodies
HM-GIM: A Probabilistic Neural Model for Discovering Heterogeneous Microbiome or Human Gene Groupings and Their Interactions
How Good is AlphaFold3 at Ranking Drug Binding Affinities?
HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generation
Ibex: Pan-immunoglobulin structure prediction
Importance-Weighted Training of Diffusion Samplers
Improving Genomic Models via Task-Specific Self-Pretraining
Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization
In silico design of epigenetic reprogramming payloads
Integrating Bilinear Transduction with Message Passing Neural Networks for Improved ADMET Property Prediction
Intrinsic Evaluation of DNA Embeddings in Genome Language Models: Insights from Yeast Genomic Sequences
JAMUN: Bridging Smoothed Molecular Dynamics and Score-Based Learning for Conformational Ensemble Generation
Joint Probabilistic Modeling of Pseudobulk and Single-Cell Transcriptomics Enables Accurate Estimation of Cell Type Composition
KODA: An agentic framework for KEGG orthology-driven discovery of antimicrobial drug targets in gut microbiome
LapDDPM: A Conditional Graph Diffusion Model for scRNA-seq Generation with Spectral Adversarial Perturbations
Learning Collective Variables from Time-lagged Generation
Learning Diffusion Models with Flexible Representation Guidance
Ligand Iterative Sampling for Affinity Refinement and Drug Discovery (LISARDD)
LLMs for Experiment Design in Scientific Domains: Are We There Yet?
Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab
Minimum-Excess-Work Guidance
MINT: Multimodal Integrated Knowledge Transfer to Large Language Models through Preference Optimization with Biomedical Applications
Mixtures of Neural Cellular Automata: A Stochastic Framework for Biological Growth Modelling
Modeling Microenvironment Trajectories on Spatial Transcriptomics with NicheFlow
Modeling Molecular Sequences with Learning-Order Autoregressive Models
Molecular Cues to Smart Sequences: Optimizing Early Round SELEX Sequences
MolFORM: Multi-modal Flow Matching for Structure-Based Drug Design
MolGuidance: A Comparative Study of Guidance Methods for Conditional Molecule Generation
Multi-Granular Contrastive Alignment and Fusion for Fragment-Enhanced Virtual Screening
Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design
Multi-Objective-Guided Generative Design of mRNA with Therapeutic Properties
Multi-state Protein Design with DynamicMPNN
Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction
No Clear Winner at Small Scale: Comparing Modern Sequence Architectures and Training Strategies for Genomic Language Models
NovoMolGen: Rethinking Molecular Language Model Pretraining
NucleoBench: A Large-Scale Benchmark of Neural Nucleic Acid Design Algorithms
OrthoGraphRAG: Enhancing Clinical Decision Making with Multi-Level Knowledge Graphs
Partition Generative Modeling: Masked Modeling Without Masks
PhenoGraph: A Multi-Agent Framework for Phenotype-driven Discovery in Spatial Transcriptomics Data Augmented with Knowledge Graphs
Pi-SAGE: Permutation-invariant surface-aware graph encoder for binding affinity prediction
Predicting function of evolutionarily implausible DNA sequences
Predicting Microbial Ontology and Pathogen Risk from Environmental Metadata with Large Language Models
Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
Promoter Sequence Generation using Homology Prompting
Protein Generator with Ribosomal Origin and Folding
ProteinCrow: A Language Model Agent That Can Design Proteins
ProVADA: Generating Subcellular Protein Variants via Ensemble-Guided Test-Time Steering
ProxelGen: Generating Proteins as 3D Densities
Pullback Flow Matching on Data Manifolds
Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator
Rapidash: Scalable Molecular Modeling Through Controlled Equivariance Breaking
Representing local protein environments with atomistic foundation models
Retrieval Augmented Protein Language Models for Protein Structure Prediction
Revisiting Sampling Strategies for Molecular Generation
Riemannian generative decoder
Robust Molecular Property Prediction via Densifying Scarce Labeled Data
Scaffold-Driven GPT Model for Drug Optimization
scAgents: A Multi-Agent Framework for Fully Autonomous End-to-End Single-Cell Perturbation Analysis
Scaling and Saturation Protein Language Models with Biological Data
Self-supervised learning predicts plant growth trajectories from multi-modal industrial greenhouse data
Self-Supervised Representation Learning for Microbiome Improves Downstream Prediction in Data-Limited Settings and Cross-Cohort Generalizability
SIMBA-GNN: Simulation-augmented Microbiome Abundance Graph Neural Network
Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression
SMICE: enhanced conformational sampling using AlphaFold and coevolutionary information
SOAPIA: Siamese-Guided Generation of Off Target-Avoiding Protein Interactions with High Target Affinity
Sparse Autoencoders in Protein Engineering Campaigns: Steering and Model Diffing
Spatial Cell-Guided Pretraining for Scalable Spatial Transcriptomics Foundation Model
Straight but not so fast: Challenges with Rectified Flows in Protein Design.
Straight-Line Diffusion Model for Efficient 3D Molecular Generation
STRAND: Structure Refinement of RNA-Protein Complexes via Diffusion
SurfProp: A surface-based property prediction framework for antibody developability and screening
SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling
SynPair: Pairing Unpaired Antibody Chains at Billion-Sequence Scale With Contrastive Learning
TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality
TACTIC: An Explainable Multi-Agent Architecture for Classification & Interpretable Reasoning in Spatial Transcriptomics
Teddy: A FAMILY OF FOUNDATION MODELS FOR UNDERSTANDING SINGLE CELL BIOLOGY
Tissue Reassembly with Generative AI
To Optimize, Not to Invent: RNAGenScape for mRNA Sequence Generation and Optimization Without de novo Design
Torsional-GFN: a conditional conformation generator for small molecules
Towards functional annotation with latent protein language model features
Towards Molecular Conformer Generation with Language Models
ToxBench: A Binding Affinity Prediction Benchmark with AB-FEP-Calculated Labels for Human Estrogen Receptor Alpha
Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics
Two-Stage Pretraining for Molecular Property Prediction in the Wild
Unifying Force Prediction and Molecular Conformation Generation Through Representation Alignment
Unlocking Non-Invasive Brain-to-Text