Molecular Contrastive Pretraining with Collaborative Featurizations | |
Yanqiao Zhu1![]() ![]() | |
发表期刊 | Journal of Chemical Information and Modeling (JCIM)
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ISSN | 1549-9596 |
2024-02-25 | |
卷号 | 64期号:4页码:1112–1122 |
通讯作者 | Wu, Shu(shu.wu@nlpr.ia.ac.cn) |
摘要 | Molecular pretraining, which learns molecular representations over massive unlabeled data, has become a prominent paradigm to solve a variety of tasks in computational chemistry and drug discovery. Recently, prosperous progress has been made in molecular pretraining with dierent molecular featurizations, including 1D SMILES strings, 2D graphs, and 3D geometries. However, the role of molecular featurizations with their corresponding neural architectures in molecular pretraining remains largely unexamined. In this paper, through two case studies—chirality classification and aromatic ring counting—we first demonstrate that dierent featurization techniques convey chemical information dierently. In light of this observation, we propose a simple and eective MOlecular pretraining framework with COllaborative featurizations (MOCO). MOCO comprehensively leverages multiple featurizations that complement each other and outperforms existing state-of-the-art models that solely relies on one or two featurizations on a wide range of molecular property prediction tasks. |
DOI | 10.1021/acs.jcim.3c01468 |
关键词[WOS] | LANGUAGE |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[2023ZD0120901] ; National Key Research and Development Program of China[62141608] ; National Key Research and Development Program of China[62206291] ; National Key Research and Development Program of China[62372454] ; National Natural Science Foundation of China |
项目资助者 | National Natural Science Foundation of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China |
WOS研究方向 | Pharmacology & Pharmacy ; Chemistry ; Computer Science |
WOS类目 | Chemistry, Medicinal ; Chemistry, Multidisciplinary ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications |
WOS记录号 | WOS:001163373600001 |
出版者 | AMER CHEMICAL SOC |
七大方向——子方向分类 | 机器学习 |
国重实验室规划方向分类 | 智能计算与学习 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/57485 |
专题 | 模式识别实验室 |
通讯作者 | Shu Wu |
作者单位 | 1.中国科学院自动化研究所 2.Cornell University 3.北京大学 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Yanqiao Zhu,Dingshuo Chen,Yuanqi Du,et al. Molecular Contrastive Pretraining with Collaborative Featurizations[J]. Journal of Chemical Information and Modeling (JCIM),2024,64(4):1112–1122. |
APA | Yanqiao Zhu,Dingshuo Chen,Yuanqi Du,Yingze Wang,Qiang Liu,&Shu Wu.(2024).Molecular Contrastive Pretraining with Collaborative Featurizations.Journal of Chemical Information and Modeling (JCIM),64(4),1112–1122. |
MLA | Yanqiao Zhu,et al."Molecular Contrastive Pretraining with Collaborative Featurizations".Journal of Chemical Information and Modeling (JCIM) 64.4(2024):1112–1122. |
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Molecular Contrastiv(1868KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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