105 citations · 115 across the 5 of their papers we have counts for
5 papers
MoFormer: Multi-objective Antimicrobial Peptide Generation Based on Conditional Transformer Joint Multi-modal Fusion Descriptor
Li Wang, Xiangzheng Fu, Jiahao Yang +5
Deep learning holds a big promise for optimizing existing peptides with more desirable properties, a critical step towards accelerating new drug discovery. Despite the recent emerg…
KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion
Tengfei Ma, Xiang song, Wen Tao +6
Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations…
DrugAssist: A Large Language Model for Molecule Optimization
Geyan Ye, Xibao Cai, Houtim Lai +5
Recently, the impressive performance of large language models (LLMs) on a wide range of tasks has attracted an increasing number of attempts to apply LLMs in drug discovery. Howeve…
DiffColor: Toward High Fidelity Text-Guided Image Colorization with Diffusion Models
Jianxin Lin, Peng Xiao, Yijun Wang +2
Recent data-driven image colorization methods have enabled automatic or reference-based colorization, while still suffering from unsatisfactory and inaccurate object-level color co…
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction
Xuan Lin, Lichang Dai, Yafang Zhou +9
Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially…