Search Results - "Hsieh, Chang Yu"

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    Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models by Jiang, Dejun, Wu, Zhenxing, Hsieh, Chang-Yu, Chen, Guangyong, Liao, Ben, Wang, Zhe, Shen, Chao, Cao, Dongsheng, Wu, Jian, Hou, Tingjun

    Published in Journal of cheminformatics (17-02-2021)
    “…Graph neural networks (GNN) has been considered as an attractive modelling method for molecular property prediction, and numerous studies have shown that GNN…”
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    A unified drug–target interaction prediction framework based on knowledge graph and recommendation system by Ye, Qing, Hsieh, Chang-Yu, Yang, Ziyi, Kang, Yu, Chen, Jiming, Cao, Dongsheng, He, Shibo, Hou, Tingjun

    Published in Nature communications (22-11-2021)
    “…Prediction of drug-target interactions (DTI) plays a vital role in drug development in various areas, such as virtual screening, drug repurposing and…”
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    TrimNet: learning molecular representation from triplet messages for biomedicine by Li, Pengyong, Li, Yuquan, Hsieh, Chang-Yu, Zhang, Shengyu, Liu, Xianggen, Liu, Huanxiang, Song, Sen, Yao, Xiaojun

    Published in Briefings in bioinformatics (01-07-2021)
    “…Abstract Motivation Computational methods accelerate drug discovery and play an important role in biomedicine, such as molecular property prediction and…”
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    Analysis of the forward-backward trajectory solution for the mixed quantum-classical Liouville equation by Hsieh, Chang-Yu, Kapral, Raymond

    Published in The Journal of chemical physics (07-04-2013)
    “…Mixed quantum-classical methods provide powerful algorithms for the simulation of quantum processes in large and complex systems. The forward-backward…”
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    An equivariant generative framework for molecular graph-structure Co-design by Zhang, Zaixi, Liu, Qi, Lee, Chee-Kong, Hsieh, Chang-Yu, Chen, Enhong

    Published in Chemical science (Cambridge) (09-08-2023)
    “…Designing molecules with desirable physiochemical properties and functionalities is a long-standing challenge in chemistry, material science, and drug…”
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    Chemistry-intuitive explanation of graph neural networks for molecular property prediction with substructure masking by Wu, Zhenxing, Wang, Jike, Du, Hongyan, Jiang, Dejun, Kang, Yu, Li, Dan, Pan, Peichen, Deng, Yafeng, Cao, Dongsheng, Hsieh, Chang-Yu, Hou, Tingjun

    Published in Nature communications (04-05-2023)
    “…Graph neural networks (GNNs) have been widely used in molecular property prediction, but explaining their black-box predictions is still a challenge. Most…”
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    Neural predictor based quantum architecture search by Zhang, Shi-Xin, Hsieh, Chang-Yu, Zhang, Shengyu, Yao, Hong

    Published in Machine learning: science and technology (01-12-2021)
    “…Variational quantum algorithms (VQAs) are widely speculated to deliver quantum advantages for practical problems under the quantum–classical hybrid…”
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    Aggravation of discoid lupus erythematosus in a patient with psoriasis and psoriatic arthritis during treatment of secukinumab: A case report and review of literature by Hsieh, Chang-Yu, Tsai, Tsen-Fang

    Published in Lupus (01-06-2022)
    “…Background The coexistence of psoriasis and cutaneous lupus erythematosus (LE) is uncommon. Treatment for concomitant psoriasis and LE is challenging because…”
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    Deep Learning for Optoelectronic Properties of Organic Semiconductors by Lu, Chengqiang, Liu, Qi, Sun, Qiming, Hsieh, Chang-Yu, Zhang, Shengyu, Shi, Liang, Lee, Chee-Kong

    Published in Journal of physical chemistry. C (02-04-2020)
    “…Atomistic modeling of the optoelectronic properties of organic semiconductors (OSCs) requires a large number of excited-state electronic-structure…”
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    A generalized protein-ligand scoring framework with balanced scoring, docking, ranking and screening powers by Shen, Chao, Zhang, Xujun, Hsieh, Chang-Yu, Deng, Yafeng, Wang, Dong, Xu, Lei, Wu, Jian, Li, Dan, Kang, Yu, Hou, Tingjun, Pan, Peichen

    Published in Chemical science (Cambridge) (02-08-2023)
    “…Applying machine learning algorithms to protein-ligand scoring functions has aroused widespread attention in recent years due to the high predictive accuracy…”
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    Acquired diffuse palmoplantar erythema with keratoderma in Chinese patients with pustular psoriasis: A predictor for IL36 receptor antagonist c.115+6T>C mutation? by Hsu, Francis Li‐Tien, Hsieh, ChangYu, Tsai, Tsen‐Fang

    Published in Experimental dermatology (01-03-2024)
    “…Several studies have suggested that mutation of the interleukin 36 receptor antagonist gene (IL36RN) is related to generalized pustular psoriasis (GPP), and…”
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    Deficiency of interleukin‐36 receptor antagonist (DITRA): An analysis of 58 Chinese patients in a tertiary hospital in Taiwan by Hsieh, ChangYu, Huang, Yi‐Wei, Huang, Yi‐Hsuan, Tsai, Tsen‐Fang

    Published in Experimental dermatology (01-08-2023)
    “…DITRA, acronym for deficiency of interleukin‐36 receptor antagonist (IL36RN), leads to unopposed pro‐inflammatory signalling which typically manifests as…”
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    Knowledge-based BERT: a method to extract molecular features like computational chemists by Wu, Zhenxing, Jiang, Dejun, Wang, Jike, Zhang, Xujun, Du, Hongyan, Pan, Lurong, Hsieh, Chang-Yu, Cao, Dongsheng, Hou, Tingjun

    Published in Briefings in bioinformatics (13-05-2022)
    “…Abstract Molecular property prediction models based on machine learning algorithms have become important tools to triage unpromising lead molecules in the…”
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    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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    CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training by Cai, Heng, Shen, Chao, Jian, Tianye, Zhang, Xujun, Chen, Tong, Han, Xiaoqi, Yang, Zhuo, Dang, Wei, Hsieh, Chang-Yu, Kang, Yu, Pan, Peichen, Ji, Xiangyang, Song, Jianfei, Hou, Tingjun, Deng, Yafeng

    Published in Chemical science (Cambridge) (24-01-2024)
    “…The expertise accumulated in deep neural network-based structure prediction has been widely transferred to the field of protein-ligand binding pose prediction,…”
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    Predictors for the effectiveness of 75 mg risankizumab in treating psoriasis—A real‐word evidence from a 52‐week retrospective study by Hsieh, ChangYu, Tseng, Yu‐Hsian, Tsai, Tsen‐Fang

    Published in Experimental dermatology (01-12-2023)
    “…In the registration trial of risankizumab for patients with moderate‐to‐severe psoriasis in Japan, similar Psoriasis Area Severity Index (PASI) responses were…”
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