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Meijing Fang

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Book Open access Aug 2026

Benchmarking LLM Agents on Real-World Biological Database Curation for Data-Driven Scientific Discovery

BioDataLab evaluates the capability of autonomous agents to transform raw, heterogeneous biological resources into structured, analysis-ready databases, and underscores that while LLMs are proficient in downstream reasoning, autonomous upstream curation remains a formidable frontier.

Jiaxian Yan, Xi Fang, Jintao Zhu et al. · 0 citations

LumiCharge: Spherical Harmonic Convolutional Networks for Atomic Charge Prediction in Drug Discovery.

This work proposes LumiCharge, a novel atomic charge prediction framework that incorporates high-order spherical harmonics convolutions and explicitly models multibody interactions, and demonstrates exceptional extrapolation capability and robustness across molecules of varying sizes, effectively overcoming the limitat...

Qun Su, Hui Zhang, Qiaolin Gou et al. · 2 citations

ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction

This work introduces an advanced equivariant graph attention neural network specifically engineered to model long-range atomic electrostatic interactions with high precision, and improves the model's accuracy, generalization, and robustness in complex scenarios.

Qiaolin Gou, Qun Su, Ji-Ke Wang et al. · 1 citation
#machine learning Open access May 2025

Token-Mol 1.0: tokenized drug design with large language models

Token-Mol is presented, a token-only 3D drug design model that encodes both 2D and 3D structural information, along with molecular properties, into discrete tokens, which introduces a Gaussian cross-entropy loss function tailored for regression tasks, enabling superior performance across multiple downstream application...

Ji-Ke Wang, Rui Qin, Mingyang Wang et al. · 30 citations · ⚡1
Book Open access Aug 2026

Benchmarking LLM Agents on Real-World Biological Database Curation for Data-Driven Scientific Discovery

High-quality biological databases are the bedrock of data-driven scientific discovery. However, the construction of these resources remains a labor-intensive bottleneck, particularly for emerging research frontiers where structured data is non-existent. While LLM-based agents have catalyzed progress in downstream scien...

Jiaxian Yan, Xi Fang, Jintao Zhu et al. · 0 citations

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