Vote for your favorite mineral in #MinCup25! - Baryte vs. Hematite
It's a heavyweight match between industrial powerhouses as soft #baryte competes against rusty red #hematite.
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

Inoue, Nanako, Shibata, Tomokazu, Tanaka, Yusuke, Taguchi, Hiromu, Sawada, Ryusuke, Goto, Kenshin, Momokita, Shogo, Aoyagi, Morihiro, Hirao, Takashi, Yamanishi, Yoshihiro (2024) Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. Journal of Chemical Information and Modeling, 64 (14) 5712-5724 doi:10.1021/acs.jcim.4c00061

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleRevealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning
JournalJournal of Chemical Information and Modeling
AuthorsInoue, NanakoAuthor
Shibata, TomokazuAuthor
Tanaka, YusukeAuthor
Taguchi, HiromuAuthor
Sawada, RyusukeAuthor
Goto, KenshinAuthor
Momokita, ShogoAuthor
Aoyagi, MorihiroAuthor
Hirao, TakashiAuthor
Yamanishi, YoshihiroAuthor
Year2024 (July 22)Volume64
Page(s)5712-5724Issue14
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.4c00061Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17506006Long-form Identifiermindat:1:5:17506006:3
GUID0
Full ReferenceInoue, Nanako, Shibata, Tomokazu, Tanaka, Yusuke, Taguchi, Hiromu, Sawada, Ryusuke, Goto, Kenshin, Momokita, Shogo, Aoyagi, Morihiro, Hirao, Takashi, Yamanishi, Yoshihiro (2024) Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. Journal of Chemical Information and Modeling, 64 (14) 5712-5724 doi:10.1021/acs.jcim.4c00061
Plain TextInoue, Nanako, Shibata, Tomokazu, Tanaka, Yusuke, Taguchi, Hiromu, Sawada, Ryusuke, Goto, Kenshin, Momokita, Shogo, Aoyagi, Morihiro, Hirao, Takashi, Yamanishi, Yoshihiro (2024) Revealing Comprehensive Food Functionalities and Mechanisms of Action through Machine Learning. Journal of Chemical Information and Modeling, 64 (14) 5712-5724 doi:10.1021/acs.jcim.4c00061
In(2024, July) Journal of Chemical Information and Modeling Vol. 64 (14) American Chemical Society (ACS)

See Also

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

Sawada, Ryusuke, Iwata, Hiroaki, Mizutani, Sayaka, Yamanishi, Yoshihiro (2015) Target-Based Drug Repositioning Using Large-Scale Chemical–Protein Interactome Data. Journal of Chemical Information and Modeling, 55 (12) 2717-2730 doi:10.1021/acs.jcim.5b00330
Iwata, Hiroaki, Sawada, Ryusuke, Mizutani, Sayaka, Kotera, Masaaki, Yamanishi, Yoshihiro (2015) Large-Scale Prediction of Beneficial Drug Combinations Using Drug Efficacy and Target Profiles. Journal of Chemical Information and Modeling, 55 (12) 2705-2716 doi:10.1021/acs.jcim.5b00444
Kaitoh, Kazuma, Yamanishi, Yoshihiro (2021) TRIOMPHE: Transcriptome-Based Inference and Generation of Molecules with Desired Phenotypes by Machine Learning. Journal of Chemical Information and Modeling, 61 (9) 4303-4320 doi:10.1021/acs.jcim.1c00967
Röcken, Sebastien; Zavadlav, Julija (2025) Enhancing Machine Learning Potentials through Transfer Learning across Chemical Elements. Journal of Chemical Information and Modeling, 65 (14). doi:10.1021/acs.jcim.5c00293
Karmakar, Tarak, Soares, Thereza A., Merz, Kenneth M. (2024) Enhancing Coarse-Grained Models through Machine Learning. Journal of Chemical Information and Modeling, 64 (8) 2931-2932 doi:10.1021/acs.jcim.4c00537
Matsukiyo, Yuki, Tengeiji, Atsushi, Li, Chen, Yamanishi, Yoshihiro (2024) Transcriptionally Conditional Recurrent Neural Network for De Novo Drug Design. Journal of Chemical Information and Modeling, 64 (15) 5844-5852 doi:10.1021/acs.jcim.4c00531
Jia, Hengjian, Sosso, Gabriele C. (2024) Transparent Machine Learning Model to Understand Drug Permeability through the Blood–Brain Barrier. Journal of Chemical Information and Modeling, 64 (23). doi:10.1021/acs.jcim.4c01217
Iwata, Hiroaki, Sawada, Ryusuke, Mizutani, Sayaka, Yamanishi, Yoshihiro (2015) Systematic Drug Repositioning for a Wide Range of Diseases with Integrative Analyses of Phenotypic and Molecular Data. Journal of Chemical Information and Modeling, 55 (2) 446-459 doi:10.1021/ci500670q
Yang, Youyou, Gan, Wenli, Lin, Lei, Wang, Long, Wu, Jianming, Luo, Jiesi (2024) Identification of Active Molecules against Thrombocytopenia through Machine Learning. Journal of Chemical Information and Modeling, 64 (16). doi:10.1021/acs.jcim.4c00718
Atasi, Chureh, Kern, Joseph, Ramprasad, Rampi (2024) Design of Recyclable Plastics with Machine Learning and Genetic Algorithm. Journal of Chemical Information and Modeling, 64 (24). doi:10.1021/acs.jcim.4c01530
Zhong, Guolun, Deng, Lei (2024) ACPScanner: Prediction of Anticancer Peptides by Integrated Machine Learning Methodologies. Journal of Chemical Information and Modeling, 64 (3) 1092-1104 doi:10.1021/acs.jcim.3c01860
 
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 19, 2025 03:04:28
Go to top of page