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Articles by Jike Wang
ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms Click to copy article link Article link copied!
Cite Jump to ExpandCollapse Machine Learning and Deep LearningJuly 13, 2026 ProphDR: An Interpretable Deep Learning Model for Predicting Cancer Drug Response via Multi-Omics and Cross-Attention Mechanisms Click to copy article linkArticle link copied! Yundian Zeng Yundian Zeng Zhejiang University, Hangzhou, Zhejiang 310058, China College of Control Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China Qing Ye Qing Ye Zhejiang University, Hangzhou, Zhejiang 310058,...
LaMGen: LLM-based 3D molecular generation for multi-target drug design
Abstract Multi-target drugs hold great promise for treating complex diseases, yet existing methodologies predominantly rely on ligand-based approaches, which lack sufficient biological context and are often confined to specific target pairs, resulting in limited generalizability. Here, we introduce LaMGen, a general-purpose multi-target drug design framework powered by large language models (LLMs).
A scalable and quantum-accurate foundation model for biomolecular force fields via linearly tensorized quadrangle attention - Nature Communications
Abstract Accurate atomistic biomolecular simulations are vital for understanding disease mechanisms and drug discovery, yet existing methods struggle to balance quantum-mechanical accuracy with computational scalability. Classical force fields often lack precision, while quantum methods are computationally prohibitive for complex biological systems.
AutoLoop is an autoregressive deep learning method for protein loop prediction with high accuracy
Keywords protein loop prediction deep learning Introduction Proteins are fundamental to life, participating in numerous biological functions.
Biology-driven insights into the power of single-cell foundation models - Genome Biology
In this study, we standardized to select 2000 highly variable genes with a predefined batch key using the Scanpy [62] Python package. Crucially, HVG selection is also part of the data processing protocols of scVI, Harmony, and scGPT. scVI [18] is a variational autoencoder (VAE)-based generative model, which is widely used in single-cell transcriptomics data analysis.
Discovery of antimicrobial peptides with notable antibacterial potency by an LLM-based foundation model
The HHS Officials Being Paid Six Figures to Do Nothing The Trump administration hasn’t fired them but won’t let them do their jobs. When she succeeded Anthony Fauci as the director of the National Institute of Allergy and Infectious Diseases, Jeanne Marrazzo felt that she’d landed “probably the most important infectious-disease job in the world,” she …
Advancing biomolecular understanding and design following human instructions
University of Michigan under federal scrutiny after arrest of Chinese scientists Probe comes after three Chinese citizens tied to the University of Michigan were accused of smuggling biological hazards into the U.S. DETROIT — The Trump administration is investigating potential foreign influence at the University of Michigan, claiming the school was indifferent to national …
Effective Generation of Heavy-Atom-Free Triplet Photosensitizers Containing Multiple Intersystem Crossing Mechanisms Based on Deep Learning
Effective Generation of Heavy-Atom-Free Triplet Photosensitizers Containing Multiple Intersystem Crossing Mechanisms Based on Deep Learning Photodynamic therapy (PDT) is a clinically approved therapeutic modality that has demonstrated significant potential for cancer treatment, and triplet photosensitizers (PSs) play a key role in its efficacy.
TRAP: A Contrastive Learning-Enhanced Framework for Robust TCR-pMHC Binding Prediction with Improved Generalizability
TRAP: A Contrastive Learning-Enhanced Framework for Robust TCR-pMHC Binding Prediction with Improved Generalizability The binding of T cell receptors (TCRs) to peptide-MHC I (pMHC) complexes is critical in triggering adaptive immunity response to potential health threats. Developing highly accurate machine learning (ML) models to predict TCR-pMHC binding could significantly accelerate immunotherapy advancements.
A Multi‐Objective Molecular Generation Method Based on Pareto Algorithm and Monte Carlo Tree Search
1 Introduction Traditional drug design methods, encompassing target identification, lead compound discovery, and subsequent optimization, are often hampered by high costs and lengthy timelines.[1] Particularly, in the initial lead discovery phase, significant investments in human and material resources are often necessary to synthesize and screen molecules.
AI‐Guided Design of Antimicrobial Peptide Hydrogels for Precise Treatment of Drug‐resistant Bacterial Infections
Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description adma202500043-sup-0001-SuppMat.docx10.1 MB Supporting Information References 1, , , Nat. Rev. Microbiol. 2024, 22, 262. 2, , , , , , , , , Small 2020, 16, 2001099. 3, , , , , , , , , , , J. Nanobiotechnology 2024, 22, 161. 4, , , , , ACS Cent. Sci. 2020, 6, 207. 5, , , , , , , , , , , Front. Pharmacol. 2021, 12, 597907. 6, , , , , , J. Hazard. Mater. 2024, 479, 135601. 7, , , , , , , Adv.
Robust Protein-Ligand Interaction Modeling through Integrating Physical Laws and Geometric Knowledge for Absolute Binding Free Energy Calculation
Robust Protein-Ligand Interaction Modeling through Integrating Physical Laws and Geometric Knowledge for Absolute Binding Free Energy Calculation Accurate estimation of protein-ligand (PL) binding free energies is a crucial task in medicinal chemistry and a critical measure of PL interaction modeling effectiveness. However, traditional computational methods are often computationally expensive and prone to errors.
3DSMILES-GPT: 3D molecular pocket-based generation with token-only large language model
3DSMILES-GPT: 3D molecular pocket-based generation with token-only large language model† The generation of three-dimensional (3D) molecules based on target structures represents a cutting-edge challenge in drug discovery. Many existing approaches often produce molecules with invalid configurations, unphysical conformations, suboptimal drug-like qualities, limited synthesizability, and require extensive generation times.
3DSMILES-GPT: 3D Molecular Pocket-based Generation with Token-only Large Language Model
3DSMILES-GPT: 3D Molecular Pocket-based Generation with Token-only Large Language Model The generation of three-dimensional (3D) molecules based on target structures represents a cutting-edge challenge in drug discovery. Many existing approaches often produce molecules with invalid configurations, unphysical conformations, suboptimal drug-like qualities, limited synthesizability, and require extensive generation times.
Genetic Algorithm-Based Receptor Ligand: A Genetic Algorithm-Guided Generative Model to Boost the Novelty and Drug-Likeness of Molecules in a Sampling Chemical Space
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Chem. Inf. Model. 2024, XXXX, XXX Terms & Conditions Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses).
CODD-Pred: A Web Server for Efficient Target Identification and Bioactivity Prediction of Small Molecules
Download Hi-Res ImageDownload to MS-PowerPointCite This:J. Chem. Inf. Model. 2023, XXXX, XXX Terms & Conditions Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses).
Engineering iron atom-cluster nanostructure towards efficient and durable electrocatalysis
Engineering iron atom-cluster nanostructure towards efficient and durable electrocatalysis Feng-Yi Zheng, Ruisong Li, Shibo Xi, Fei Ai and Jike Wang Abstract Iron-based catalysts have demonstrated their fascinating activities in oxygen reduction reaction (ORR), especially for the synergistic effect between atoms and clusters, but challenging for further improvement.
SDEGen: Learning to Evolve Molecular Conformations from Thermodynamic Noise for Conformation Generation
SDEGen: Learning to Evolve Molecular Conformations from Thermodynamic Noise for Conformation Generation Haotian Zhang, Shengming Li, Jintu Zhang, zhe wang, Jike Wang, Dejun Jiang, Zhiwen Bian, Yixue Zhang, Yafeng Deng, Jianfei Song, Yu Kang and Tingjun Hou Abstract Generation of representative conformations for small molecules is a fundamental task in cheminformatics and computer-aided drug discovery, but capturing the complex distribution of conformations that contains multiple low energy...
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