Optimizing Mirror-Image Peptide Sequence Design for Data Storage via Peptide Bond Cleavage Prediction
Fuente:
arXiv
Saved in:
| Main Authors: | Lu, Yilong, Chen, Si, Gao, Songyan, Liu, Han, Dong, Xin, Shen, Wenfeng, Ding, Guangtai |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision
by: Shah, Aayush, et al.
Published: (2024)
by: Shah, Aayush, et al.
Published: (2024)
Leveraging Machine Learning Models for Peptide-Protein Interaction Prediction
by: Yin, Song, et al.
Published: (2023)
by: Yin, Song, et al.
Published: (2023)
HMAMP: Hypervolume-Driven Multi-Objective Antimicrobial Peptides Design
by: Wang, Li, et al.
Published: (2024)
by: Wang, Li, et al.
Published: (2024)
Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
by: Chen, Shaorong, et al.
Published: (2026)
by: Chen, Shaorong, et al.
Published: (2026)
DREAM-B3P: Dual-Stream Transformer Network Enhanced by Feedback Diffusion Model for Blood-Brain Barrier Penetrating Peptide Prediction
by: Wang, Kaijie, et al.
Published: (2025)
by: Wang, Kaijie, et al.
Published: (2025)
NovoBench: Benchmarking Deep Learning-based De Novo Peptide Sequencing Methods in Proteomics
by: Zhou, Jingbo, et al.
Published: (2024)
by: Zhou, Jingbo, et al.
Published: (2024)
AdaNovo: Adaptive \emph{De Novo} Peptide Sequencing with Conditional Mutual Information
by: Xia, Jun, et al.
Published: (2024)
by: Xia, Jun, et al.
Published: (2024)
Stochastic Model of siRNA Endosomal Escape Mediated by Fusogenic Peptides in OVCAR-3
by: Yadav, Nisha, et al.
Published: (2024)
by: Yadav, Nisha, et al.
Published: (2024)
Beyond Current Boundaries: Integrating Deep Learning and AlphaFold for Enhanced Protein Structure Prediction from Low-Resolution Cryo-EM Maps
by: Xin, et al.
Published: (2024)
by: Xin, et al.
Published: (2024)
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties
by: Badrinarayanan, Srivathsan, et al.
Published: (2024)
by: Badrinarayanan, Srivathsan, et al.
Published: (2024)
ProDCARL: Reinforcement Learning-Aligned Diffusion Models for De Novo Antimicrobial Peptide Design
by: Sheng, Fang, et al.
Published: (2026)
by: Sheng, Fang, et al.
Published: (2026)
Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations
by: Qi, Cong, et al.
Published: (2025)
by: Qi, Cong, et al.
Published: (2025)
THFlow: A Temporally Hierarchical Flow Matching Framework for 3D Peptide Design
by: Huang, Dengdeng, et al.
Published: (2025)
by: Huang, Dengdeng, et al.
Published: (2025)
A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation
by: Wang, Yongkang, et al.
Published: (2023)
by: Wang, Yongkang, et al.
Published: (2023)
GROOT: Effective Design of Biological Sequences with Limited Experimental Data
by: Tran, Thanh V. T., et al.
Published: (2024)
by: Tran, Thanh V. T., et al.
Published: (2024)
iBitter-Stack: A Multi-Representation Ensemble Learning Model for Accurate Bitter Peptide Identification
by: Ahmad, Sarfraz, et al.
Published: (2025)
by: Ahmad, Sarfraz, et al.
Published: (2025)
DapPep: Domain Adaptive Peptide-agnostic Learning for Universal T-cell Receptor-antigen Binding Affinity Prediction
by: Zheng, Jiangbin, et al.
Published: (2024)
by: Zheng, Jiangbin, et al.
Published: (2024)
Optimization of Bloch-Siegert B1 Mapping Sequence for Maximum Signal to Noise
by: Khalighi, M. Mehdi, et al.
Published: (2024)
by: Khalighi, M. Mehdi, et al.
Published: (2024)
An Evolutionary Approach for Designing Stable and Highly Expressible Low-Immunogenicity Therapeutic mRNA Sequences
by: Dong, Dhawa Sang, et al.
Published: (2026)
by: Dong, Dhawa Sang, et al.
Published: (2026)
ProtT-Affinity: Sequence-Based Protein-Protein Binding Affinity Prediction Using ProtT5 Embeddings
by: Lou, Hongfu
Published: (2025)
by: Lou, Hongfu
Published: (2025)
SynCraft: Guiding Large Language Models to Predict Edit Sequences for Molecular Synthesizability Optimization
by: Li, Junren, et al.
Published: (2025)
by: Li, Junren, et al.
Published: (2025)
Exploring Latent Space for Generating Peptide Analogs Using Protein Language Models
by: Liang, Po-Yu, et al.
Published: (2024)
by: Liang, Po-Yu, et al.
Published: (2024)
Drug Resistance Predictions Based on a Directed Flag Transformer
by: Chen, Dong, et al.
Published: (2024)
by: Chen, Dong, et al.
Published: (2024)
Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks
by: Chen, Angelica, et al.
Published: (2024)
by: Chen, Angelica, et al.
Published: (2024)
Machine Learning-Based Prediction of Mortality in Geriatric Traumatic Brain Injury Patients
by: Si, Yong, et al.
Published: (2025)
by: Si, Yong, et al.
Published: (2025)
GoForth: Language Models for RNA Design under Structure, Sequence, and Coding Constraints
by: Lindsey, Michael
Published: (2026)
by: Lindsey, Michael
Published: (2026)
Frequency-Space Mechanics: A Sequence and Coordinate-Free Representation for Protein Function Prediction
by: Reilly, Charles B
Published: (2026)
by: Reilly, Charles B
Published: (2026)
Decoupled Sequence and Structure Generation for Realistic Antibody Design
by: Kim, Nayoung, et al.
Published: (2024)
by: Kim, Nayoung, et al.
Published: (2024)
Physics-Guided Surrogate Modeling for Machine Learning-Driven DLD Design Optimization
by: Islam, Khayrul, et al.
Published: (2025)
by: Islam, Khayrul, et al.
Published: (2025)
Uncovering the Genetic Basis of Glioblastoma Heterogeneity through Multimodal Analysis of Whole Slide Images and RNA Sequencing Data
by: Berjaoui, Ahmad, et al.
Published: (2024)
by: Berjaoui, Ahmad, et al.
Published: (2024)
An Active Learning Framework for Data-Efficient, Human-in-the-Loop Enzyme Function Prediction
by: Babjac, Ashley, et al.
Published: (2026)
by: Babjac, Ashley, et al.
Published: (2026)
A Regressor-Guided Graph Diffusion Model for Predicting Enzyme Mutations to Enhance Turnover Number
by: Yu, Xiaozhu, et al.
Published: (2024)
by: Yu, Xiaozhu, et al.
Published: (2024)
Is Sequence Information All You Need for Bayesian Optimization of Antibodies?
by: Ober, Sebastian W., et al.
Published: (2025)
by: Ober, Sebastian W., et al.
Published: (2025)
How Mathematical Forms of Chemotherapy and Radiotherapy Bias Model-Optimized Predictions: Implications for Model Selection
by: Oh, Changin, et al.
Published: (2025)
by: Oh, Changin, et al.
Published: (2025)
SynCell: Contextualized Drug Synergy Prediction
by: Peng, Keqin, et al.
Published: (2025)
by: Peng, Keqin, et al.
Published: (2025)
Deep Learning for Blood-Brain Barrier Permeability Prediction: From Discriminative Models to Mechanism-Aware Design
by: Yang, Zihan, et al.
Published: (2025)
by: Yang, Zihan, et al.
Published: (2025)
Omni-QALAS: Optimized Multiparametric Imaging for Simultaneous T1, T2 and Myelin Water Mapping
by: Li, Shizhuo, et al.
Published: (2025)
by: Li, Shizhuo, et al.
Published: (2025)
VADA: a Data-Driven Simulator for Nanopore Sequencing
by: Niederle, Jonas, et al.
Published: (2024)
by: Niederle, Jonas, et al.
Published: (2024)
UNGT: Ultrasound Nasogastric Tube Dataset for Medical Image Analysis
by: Liu, Zhaoshan, et al.
Published: (2025)
by: Liu, Zhaoshan, et al.
Published: (2025)
Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences
by: Kim, Minsu, et al.
Published: (2023)
by: Kim, Minsu, et al.
Published: (2023)
Similar Items
-
Peptide-GPT: Generative Design of Peptides using Generative Pre-trained Transformers and Bio-informatic Supervision
by: Shah, Aayush, et al.
Published: (2024) -
Leveraging Machine Learning Models for Peptide-Protein Interaction Prediction
by: Yin, Song, et al.
Published: (2023) -
HMAMP: Hypervolume-Driven Multi-Objective Antimicrobial Peptides Design
by: Wang, Li, et al.
Published: (2024) -
Regressor-guided Diffusion Model for De Novo Peptide Sequencing with Explicit Mass Control
by: Chen, Shaorong, et al.
Published: (2026) -
DREAM-B3P: Dual-Stream Transformer Network Enhanced by Feedback Diffusion Model for Blood-Brain Barrier Penetrating Peptide Prediction
by: Wang, Kaijie, et al.
Published: (2025)