Search Results - "Ruiqiang Lu"

Introducing block design in graph neural networks for molecular properties prediction by Li, Yuquan, Li, Pengyong, Yang, Xing, Hsieh, Chang-Yu, Zhang, Shengyu, Wang, Xiaorui, Lu, Ruiqiang, Liu, Huanxiang, Yao, Xiaojun

“…•An algorithm named block-based graph neural network (BGNN) was proposed.•BGNN can reduce the impact of the network degradation problem.•BGNN can get lower MAE…”
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Identification of LRRK2 Inhibitors through Computational Drug Repurposing by Tan, Shuoyan, Lu, Ruiqiang, Yao, Dahong, Wang, Jun, Gao, Peng, Xie, Guotong, Liu, Huanxiang, Yao, Xiaojun

“…Parkinson’s disease (PD) is the second most common neurodegenerative disorder that affects more than ten million people worldwide. However, the current PD…”
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An Agent Based Approach for Multi-Objective Optimization in Production Scheduling for Turbine Engine Blade Manufacturing by Lu, Ruiqiang

“…With the development of many new technologies in aircraft manufacturing area and the increasing competition of the global market, aircraft manufacturing…”
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Improving drug-target affinity prediction via feature fusion and knowledge distillation by Lu, Ruiqiang, Wang, Jun, Li, Pengyong, Li, Yuquan, Tan, Shuoyan, Pan, Yiting, Liu, Huanxiang, Gao, Peng, Xie, Guotong, Yao, Xiaojun

“…Abstract Rapid and accurate prediction of drug-target affinity can accelerate and improve the drug discovery process. Recent studies show that deep learning…”
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3DSGIMD: An accurate and interpretable molecular property prediction method using 3D spatial graph focusing network and structure-based feature fusion by Tian, Yanan, Wang, Chenbin, Lu, Ruiqiang, Tong, Henry H.Y., Gong, Xiaoqing, Qiu, Jiayue, Peng, Shaoliang, Yao, Xiaojun, Liu, Huanxiang

“…A comprehensive representation of molecular structure is essential for establishing accurate and reliable molecular property prediction models. However, fully…”
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Development, validation, and evaluation of a deep learning model to screen cyclin-dependent kinase 12 inhibitors in cancers by Wen, Tingyu, Wang, Jun, Lu, Ruiqiang, Tan, Shuoyan, Li, Pengyong, Yao, Xiaojun, Liu, Huanxiang, Yi, Zongbi, Li, Lixi, Liu, Shuning, Gao, Peng, Qian, Haili, Xie, Guotong, Ma, Fei

“…Deep learning-based in silico alternatives have been demonstrated to be of significant importance in the acceleration of the drug discovery process and…”
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A deep learning approach for rational ligand generation with toxicity control via reactive building blocks by Li, Pengyong, Zhang, Kaihao, Liu, Tianxiao, Lu, Ruiqiang, Chen, Yangyang, Yao, Xiaojun, Gao, Lin, Zeng, Xiangxiang

“…Deep generative models are gaining attention in the field of de novo drug design. However, the rational design of ligand molecules for novel targets remains…”
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An adaptive graph learning method for automated molecular interactions and properties predictions by Li, Yuquan, Hsieh, Chang-Yu, Lu, Ruiqiang, Gong, Xiaoqing, Wang, Xiaorui, Li, Pengyong, Liu, Shuo, Tian, Yanan, Jiang, Dejun, Yan, Jiaxian, Bai, Qifeng, Liu, Huanxiang, Zhang, Shengyu, Yao, Xiaojun

“…Improving drug discovery efficiency is a core and long-standing challenge in drug discovery. For this purpose, many graph learning methods have been developed…”
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A novel agent bidding based optimization approach in manufacturing planning and scheduling by Ruiqiang Lu, Zhang, D Z

“…The problem of process planning and scheduling in manufacturing systems can be simply concluded as an optimization problem in terms of minimizing processing…”
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