Cover Image

Decoupled Sequence and Structure Generation for Realistic Antibody Design

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Nayoung, Kim, Minsu, Ahn, Sungsoo, Park, Jinkyoo
Format:	Preprint
Published:	2024
Subjects:	Quantitative Methods Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences
by: Kim, Minsu, et al.
Published: (2023)

Can LLMs Generate Diverse Molecules? Towards Alignment with Structural Diversity
by: Jang, Hyosoon, et al.
Published: (2024)

MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
by: Kim, Nayoung, et al.
Published: (2024)

Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
by: Ober, Sebastian W., et al.
Published: (2025)

Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
by: Kim, Hyeonah, et al.
Published: (2026)

Generative Humanization for Therapeutic Antibodies
by: Gordon, Cade, et al.
Published: (2024)

Sequence-Only Prediction of Binding Affinity Changes: A Robust and Interpretable Model for Antibody Engineering
by: Liu, Chen, et al.
Published: (2025)

BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization
by: Rao, Jackie, et al.
Published: (2026)

Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization
by: Kim, Hyeonah, et al.
Published: (2023)

EPO: Diverse and Realistic Protein Ensemble Generation via Energy Preference Optimization
by: Sun, Yuancheng, et al.
Published: (2025)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models
by: Kulytė, Paulina, et al.
Published: (2024)

Llama-Affinity: A Predictive Antibody Antigen Binding Model Integrating Antibody Sequences with Llama3 Backbone Architecture
by: Hossain, Delower, et al.
Published: (2025)

AntibodyFlow: Normalizing Flow Model for Designing Antibody Complementarity-Determining Regions
by: Xu, Bohao, et al.
Published: (2024)

Biologically-Grounded Multi-Encoder Architectures as Developability Oracles for Antibody Design
by: Crouzet, Simon J.
Published: (2026)

GROOT: Effective Design of Biological Sequences with Limited Experimental Data
by: Tran, Thanh V. T., et al.
Published: (2024)

Improving Antibody Humanness Prediction using Patent Data
by: Ucar, Talip, et al.
Published: (2024)

Curriculum-Augmented GFlowNets For mRNA Sequence Generation
by: Laajil, Aya, et al.
Published: (2025)

Multi-Modality Representation Learning for Antibody-Antigen Interactions Prediction
by: Guo, Peijin, et al.
Published: (2025)

Optimizing Mirror-Image Peptide Sequence Design for Data Storage via Peptide Bond Cleavage Prediction
by: Lu, Yilong, et al.
Published: (2025)

Reward-Guided Discrete Diffusion via Clean-Sample Markov Chain for Molecule and Biological Sequence Design
by: Phunyaphibarn, Prin, et al.
Published: (2026)

PRISM: Enhancing Protein Inverse Folding through Fine-Grained Retrieval on Structure-Sequence Multimodal Representations
by: Mahbub, Sazan, et al.
Published: (2025)

ATTNSOM: Learning Cross-Isoform Attention for Cytochrome P450 Site-of-Metabolism
by: Kim, Hajung, et al.
Published: (2026)

General Protein Pretraining or Domain-Specific Designs? Benchmarking Protein Modeling on Realistic Applications
by: Yan, Shuo, et al.
Published: (2025)

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics
by: Iyengar, Aniketh, et al.
Published: (2026)

Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization
by: Wu, Lirong, et al.
Published: (2024)

Sequence Analysis Using the Bezier Curve
by: Murad, Taslim, et al.
Published: (2025)

AbAffinity: A Large Language Model for Predicting Antibody Binding Affinity against SARS-CoV-2
by: Ashraf, Faisal Bin, et al.
Published: (2026)

VADA: a Data-Driven Simulator for Nanopore Sequencing
by: Niederle, Jonas, et al.
Published: (2024)

Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision
by: Shah, Aayush, et al.
Published: (2024)

Property-Isometric Variational Autoencoders for Sequence Modeling and Design
by: Sadeghi, Elham, et al.
Published: (2025)

Explicit Path CGR: Maintaining Sequence Fidelity in Geometric Representations
by: Ali, Sarwan
Published: (2025)

Pathway-Guided Optimization of Deep Generative Molecular Design Models for Cancer Therapy
by: Qayyum, Alif Bin Abdul, et al.
Published: (2024)

A Universal Non-Parametric Approach For Improved Molecular Sequence Analysis
by: Ali, Sarwan, et al.
Published: (2024)

ImmSET: Sequence-Based Predictor of TCR-pMHC Specificity at Scale
by: Noceda, Marco Garcia, et al.
Published: (2026)

Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design
by: Abeer, A N M Nafiz, et al.
Published: (2024)

Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design
by: Campbell, Andrew, et al.
Published: (2024)

SeqProFT: Sequence-only Protein Property Prediction with LoRA Finetuning
by: Zhang, Shuo, et al.
Published: (2024)

Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks
by: Chen, Angelica, et al.
Published: (2024)

Ankh3: Multi-Task Pretraining with Sequence Denoising and Completion Enhances Protein Representations
by: Alsamkary, Hazem, et al.
Published: (2025)

Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
by: Chen, Shaorong, et al.
Published: (2026)