Accepted Papers
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Poster
San Diego
Exploring simulators for particle picking in cryo-electron tomography
Serena Arghittu et al.
Poster
Copenhagen
Leveraging in Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization
Jackie Rao et al.
Poster
Copenhagen
Self Distillation Fine-Tuning of Protein Language Models Improves Versatility in Protein Design
Amin Tavakoli et al.
Poster
San Diego
REPTRA: Mapping Immune T Cell Receptor Activity from Full Sequences with a Debiased Contrastive Loss
John Abel et al.
Poster
San Diego
Reciprocal Best Matching: a new pipeline for scoring models with unknown stoichiometry in CASP experiments
Rongqing Yuan et al.
Contributed talk
Copenhagen
AbTune: layer-wise selective Fine-Tuning of protein language models for Antibodies
Xiaotong Xu
Poster
San Diego
Adapting Co-Folding Models for Structure-Based Protein-Protein Docking Through Flow Matching
Da Xu et al.
Poster
San Diego
Improved Therapeutic Antibody Reformatting through Multimodal Machine Learning
Jiayi Xin et al.
Poster
San Diego
ChromWeave: Equivariant Generative Modeling of 3D Genome Organization
Shuming Liu et al.
Poster
San Diego
SimpleFold: Folding Proteins is Simpler than You Think
Yuyang Wang et al.
Poster
San Diego
Learning residue level protein dynamics with multiscale Gaussians
Mihir Bafna et al.
Poster
San Diego
Generating functional and multistate proteins with a multimodal diffusion transformer
Bowen Jing et al.
Poster
Copenhagen
g-DPO: Scalable Preference Optimization for Protein Language Models
Constance Ferragu et al.
Poster
Copenhagen
A deep learning approach for rational affinity maturation of anti-VEGF nanobodies
Gaëlle Verdon et al.
Poster
San Diego
PairSAE: Mechanistic Interpretability from Pair Representations in Protein Co-Folding
Giosue Migliorini et al.
Poster
San Diego
Improved De Novo Peptide Binder Design with Target-Conditioned Inverse Folding
Elliot Layne et al.
Poster
San Diego
Conditional Protein Structure Generation with Protpardelle-1c
Tianyu Lu et al.
Poster
San Diego
MSACLR: Contrastive Learning of Protein Conformations from MSAs
JUNJIE ZHANG et al.
Contributed talk
San Diego
Ensemble-conditioned protein sequence design with Caliby
Richard Shuai et al.
Poster
Copenhagen
Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets
Chang Liu et al.
Contributed talk
Copenhagen
Computational Design of Monomeric Variants of Multimeric Enzymes
Jakub Lála et al.
Poster
Copenhagen
SynthFormer: Equivariant Pharmacophore-based Generation of Synthesizable Molecules for Ligand-Based Drug Design
Zygimantas Jocys et al.
Poster
Copenhagen
Stoic: Fast and accurate protein stoichiometry prediction
Daniil Litvinov et al.
Poster
San Diego
De novo generation of functional terpene synthases using TpsGPT
Hamsini Ramanathan et al.
Contributed talk
Copenhagen
ProteomeLM: A proteome-scale language model enables accurate and rapid prediction of protein-protein interactions
Cyril Malbranke et al.
Poster
Copenhagen
PrOMet: Accurate and Robust Metal-binding site and Type Prediction
Gangeun Park et al.
Contributed talk
Copenhagen
Rewriting protein alphabets with language models
Lorenzo Pantolini et al.
Poster
San Diego
Design of peptides with non-canonical amino acids using flow matching
Jin Sub Lee et al.
Poster
San Diego
FALCON: Few-step Accurate Likelihoods for Continuous Flows
Danyal Rehman et al.
Poster
Copenhagen
Improving RNA 3D Structure Prediction via Language Model-Augmented AlphaFold 3
Shuxian Zou et al.
Poster
San Diego
Look mom, no experimental data! Learning to score protein-ligand interactions from simulations
Michael Brocidiacono et al.
Poster
San Diego
forge: sequence-based binder design with latent flow matching
Young Su Ko
Poster
San Diego
FlashAffinity: Bridging the Accuracy-Speed Gap in Protein-Ligand Binding Affinity Prediction
Songlin Jiang et al.
Poster
Copenhagen
Synthetic Evolution of Enzyme Specificity with a Self-Driving Laboratory
Coban Brooks et al.
Poster
San Diego
Do biological autoregressive models learn protein coevolution?
Xiaonan Liu
Contributed talk
San Diego
SwitchCraft: Programmatic Design of State-Switching Proteins
Bowen Jing et al.
Poster
San Diego
Backprop-based Motif Scaffolding Beats Generative Models
Anisha Parsan et al.
Poster
San Diego
Conformational Rank Conditioned Committees for Machine Learning-Assisted Directed Evolution
Mia Adler et al.
Poster
San Diego
Inferring Local Protein Structural Similarity from Sequence Alone
Zinnia Ma et al.
Poster
San Diego
DiffAlign: Diffusion-Based Molecular Alignment with Pocket-Aware Guidance
Iljung Kim et al.
Poster
San Diego
BioBlobs: Differentiable Graph Partitioning for Protein Representation Learning
Xin Wang et al.
Poster
San Diego
OMTRA: A Multi-Task Generative Model for Structure-Based Drug Design
Ian Dunn et al.
Poster
San Diego
Improving scoring functions for protein-protein docking with LambdaLoss
Richard Zhu et al.
Poster
San Diego
All-atom protein design via SE(3) flow matching with ProteinZen
Alex Li et al.
Contributed talk
San Diego
Can Biomolecular Structure Predictors Generalize to Alternative Conformations?
Karson Chrispens et al.
Poster
San Diego
Biophysical Priors Enhance Protein-Protein Binding DDG Prediction
Antoine Maechler et al.
Contributed talk
San Diego
TaxoFormer: Hierarchical Transformer for Predicting the Full Taxonomic Lineage of Protein Sequences
Mohammad Parsa et al.
Poster
Copenhagen
Structure-Aware Mapping of Disease-Relevant Missense Variation: A Case Study in Three Nuclear Pore Complex Genes
Fatemeh Yekeh Yazdandoost et al.
Poster
San Diego
FlexVASP-S: Flexible Steric-Aware 3D Geometric Framework for Explaining Protein Binding Specificity
Yangying Liu et al.
Poster
San Diego
Improving nanobody structure prediction with self-distillation
Montader Ali et al.
Poster
San Diego
TangledFeatures: Robust Feature Selection in Highly Correlated Spaces
Allen Sunny
Poster
San Diego
Curriculum-Augmented GFlowNets For mRNA Sequence Generation
Aya Laajil et al.
Contributed talk
Copenhagen
ProFam: an open protein family language model for functional protein design
Jude Wells et al.
Poster
Copenhagen
MomeDTA: Improving Generalizability in Drug-Target Affinity Prediction by Mixture of Multi-view Experts
Qingyu Yang et al.
Poster
Copenhagen
On fine-tuning Boltz-2 for protein-protein affinity prediction
James King et al.
Poster
San Diego
Mechanistic Interpretability of Antibody Language Models Using SAEs
Rebonto Haque et al.
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