Vote for your favorite mineral in #MinCup25! - Cuprosklodowskite vs. Ikaite
It's radioactive #cuprosklodowskite vs ephemeral #ikaite for today's match.
Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Chen, Wei, Chen, Guanxing, Zhao, Lu, Chen, Calvin Yu-Chian (2021) Predicting Drug–Target Interactions with Deep-Embedding Learning of Graphs and Sequences. The Journal of Physical Chemistry A, 125 (25) 5633-5642 doi:10.1021/acs.jpca.1c02419

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitlePredicting Drug–Target Interactions with Deep-Embedding Learning of Graphs and Sequences
JournalThe Journal of Physical Chemistry A
AuthorsChen, WeiAuthor
Chen, GuanxingAuthor
Zhao, LuAuthor
Chen, Calvin Yu-ChianAuthor
Year2021 (July 1)Volume125
Issue25
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jpca.1c02419Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID13251134Long-form Identifiermindat:1:5:13251134:8
GUID0
Full ReferenceChen, Wei, Chen, Guanxing, Zhao, Lu, Chen, Calvin Yu-Chian (2021) Predicting Drug–Target Interactions with Deep-Embedding Learning of Graphs and Sequences. The Journal of Physical Chemistry A, 125 (25) 5633-5642 doi:10.1021/acs.jpca.1c02419
Plain TextChen, Wei, Chen, Guanxing, Zhao, Lu, Chen, Calvin Yu-Chian (2021) Predicting Drug–Target Interactions with Deep-Embedding Learning of Graphs and Sequences. The Journal of Physical Chemistry A, 125 (25) 5633-5642 doi:10.1021/acs.jpca.1c02419
In(2021, July) The Journal of Physical Chemistry A Vol. 125 (25) American Chemical Society (ACS)

See Also

These are possibly similar items as determined by title/reference text matching only.

Lv, Qiujie, Chen, Guanxing, He, Haohuai, Yang, Ziduo, Zhao, Lu, Chen, Hsin-Yi, Chen, Calvin Yu-Chian (2023) TCMBank: bridges between the largest herbal medicines, chemical ingredients, target proteins, and associated diseases with intelligence text mining. Chemical Science, 14 (39) 10684-10701 doi:10.1039/d3sc02139d
Yang, Ziduo, Zhong, Weihe, Zhao, Lu, Yu-Chian Chen, Calvin (2022) MGraphDTA: deep multiscale graph neural network for explainable drug–target binding affinity prediction. Chemical Science, 13 (3) 816-833 doi:10.1039/d1sc05180f
He, Haohuai, Chen, Guanxing, Chen, Calvin Yu-Chian (2022) Machine learning and graph neural network for finding potential drugs related to multiple myeloma. New Journal of Chemistry, 46 (11) 5188-5200 doi:10.1039/d1nj04935f
Zhang, Erdong; Pan, Zilin; Yao, Zequan; Dong, Tiejun; Chen, Guanxing; Deng, Tingwen; Chen, Shiwei; Chen, Calvin Yu-Chian (2025) Pre-trained language models for protein and molecular design. Physical Chemistry Chemical Physics, 27 (27). doi:10.1039/d5cp00785b
Li, Jun-Yan, Chen, Hsin-Yi, Dai, Wen-jie, Lv, Qiu-Jie, Chen, Calvin Yu-Chian (2019) Artificial Intelligence Approach To Investigate the Longevity Drug. The Journal of Physical Chemistry Letters, 10 (17). 4947-4961 doi:10.1021/acs.jpclett.9b02220
Jiang, Zhi-Yu, Chen, Teng-Teng, Chen, Wei-Jia, Li, Wan-Lu, Li, Jun, Wang, Lai-Sheng (2021) Expanded Inverse-Sandwich Complexes of Lanthanum Borides: La2B10– and La2B11–. The Journal of Physical Chemistry A, 125 (12) 2622-2630 doi:10.1021/acs.jpca.1c01149
Yang, Ziduo, Zhong, Weihe, Lv, Qiujie, Chen, Calvin Yu-Chian (2022) Multitask deep learning with dynamic task balancing for quantum mechanical properties prediction. Physical Chemistry Chemical Physics, 24 (9) 5383-5393 doi:10.1039/d1cp05172e
Tang, Zhenchao, Chen, Guanxing, Chen, Shouzhi, Yao, Jianhua, You, Linlin, Chen, Calvin Yu-Chian (2024) Modal-nexus auto-encoder for multi-modality cellular data integration and imputation. Nature Communications, 15 (1). doi:10.1038/s41467-024-53355-6
He, Haohuai, He, Bing, Guan, Lei, Zhao, Yu, Jiang, Feng, Chen, Guanxing, Zhu, Qingge, Chen, Calvin Yu-Chian, Li, Ting, Yao, Jianhua (2024) De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model. Nature Communications, 15 (1) doi:10.1038/s41467-024-50903-y
Rydzewski, Jakub, Valsson, Omar (2021) Multiscale Reweighted Stochastic Embedding: Deep Learning of Collective Variables for Enhanced Sampling. The Journal of Physical Chemistry A, 125 (28) 6286-6302 doi:10.1021/acs.jpca.1c02869
Wang, Guishen, Zhang, Hangchen, Shao, Mengting, Sun, Shisen, Cao, Chen (2025) MMPD-DTA: Integrating Multi-Modal Deep Learning with Pocket-Drug Graphs for Drug-Target Binding Affinity Prediction. Journal of Chemical Information and Modeling, 65 (3). doi:10.1021/acs.jcim.4c01528
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: September 14, 2025 16:03:50
Go to top of page