Hongliang Duan
Orcid: 0000-0003-3633-7855
According to our database1,
Hongliang Duan authored at least 21 papers
between 2019 and 2026.
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Bibliography
2026
HighMPNN: A Graph Neural Network Approach for Structure-Constrained Cyclic Peptide Sequence Design.
IEEE J. Biomed. Health Informatics, May, 2026
High-PepBinder: A pLM-Guided Latent Diffusion Framework for Affinity-Aware Target-Specific Peptide Design.
J. Chem. Inf. Model., 2026
HighFold-MeD2: An Enhanced Boltz-2 Model for Accurate Structure Prediction of N-Methylated and d -Amino Acid Cyclic Peptides.
J. Chem. Inf. Model., 2026
RA2M-UNet: Efficient medical image segmentation via reparameterized convolution, dual-domain attention and 2D state-space modeling.
Biomed. Signal Process. Control., 2026
MIFNDRA: an innovative knowledge-enhanced multimodal fusion and graph learning framework for predicting drug resistance-related ncRNAs.
Briefings Bioinform., 2026
HighRes_Builder: improved access and modeling of noncanonical residues for protein structure prediction.
Briefings Bioinform., 2026
2025
HighFold-MeD: a Rosetta distillation model to accelerate structure prediction of cyclic peptides with backbone N-methylation and d-amino acids.
J. Cheminformatics, December, 2025
Predicting the structures of cyclic peptides containing unnatural amino acids by HighFold2.
Briefings Bioinform., May, 2025
CycleDesigner: Leveraging CycRFdiffusion and HighFold to Design Cyclic Peptide Binders for Specific Targets.
J. Chem. Inf. Model., 2025
AlphaFold3 for Noncanonical Cyclic Peptide Modeling: Hierarchical Benchmarking Reveals Accuracy and Practical Guidelines.
J. Chem. Inf. Model., 2025
BridgeNet: a high-efficiency framework integrating sequence and structure for protein and enzyme function prediction.
Briefings Bioinform., 2025
Accurate structure prediction of cyclic peptides containing unnatural amino acids using HighFold3.
Briefings Bioinform., 2025
2024
Transfer learning across different chemical domains: virtual screening of organic materials with deep learning models pretrained on small molecule and chemical reaction data.
J. Cheminformatics, December, 2024
GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.
Briefings Bioinform., July, 2024
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.
Briefings Bioinform., May, 2024
NanoCon: contrastive learning-based deep hybrid network for nanopore methylation detection.
Bioinform., February, 2024
2023
Efficient Computational Framework for Target-Specific Active Peptide Discovery: A Case Study on IL-17C Targeting Cyclic Peptides.
J. Chem. Inf. Model., December, 2023
2022
Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios.
J. Chem. Inf. Model., 2022
From theory to experiment: transformer-based generation enables rapid discovery of novel reactions.
J. Cheminformatics, 2022
2021
Outage Performance of Full-Duplex Relay Networks Powered by RF Power Station in Ubiquitous Electric Internet of Things.
Wirel. Commun. Mob. Comput., 2021
2019
Retrosynthesis with Attention-Based NMT Model and Chemical Analysis of the "Wrong" Predictions.
CoRR, 2019