How to approach machine learning-based prediction of drug/compound–target interactions
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1758-2946
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
How to approach machine learning-based prediction of drug/compound–target interactions ; volume:15 ; number:1 ; day:6 ; month:2 ; year:2023 ; pages:1-36 ; date:12.2023
Journal of cheminformatics ; 15, Heft 1 (6.2.2023), 1-36, 12.2023
- Urheber
-
Atas Guvenilir, Heval
Doğan, Tunca
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13321-023-00689-w
- URN
-
urn:nbn:de:101:1-2023041021110322824609
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:52 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Atas Guvenilir, Heval
- Doğan, Tunca
- SpringerLink (Online service)
Ähnliche Objekte (12)
Machine Learning–Based Identification of Target Groups for Thrombectomy in Acute Stroke
A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles
Users & Machine Learning-based Curation Systems
Machine learning-based available bandwidth estimation
Machine learning-based test smell detection
WorMachine: machine learning-based phenotypic analysis tool for worms
Supervised machine learning-based Hall thruster scaling
Machine Learning-Based Analysis of Bird Vocalizations
Machine Learning-Based Scheduling in Steel Manufacturing
Prediction of compound-target interactions of natural products using large-scale drug and protein information
Deep learning-based lightweight radar target detection method
Machine learning-based quantitative prediction of drug exposure in drug-drug interactions using drug label information
Machine Learning–Based Identification of Target Groups for Thrombectomy in Acute Stroke
A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles
Users & Machine Learning-based Curation Systems
Machine learning-based available bandwidth estimation
Machine learning-based test smell detection
WorMachine: machine learning-based phenotypic analysis tool for worms
Supervised machine learning-based Hall thruster scaling
Machine Learning-Based Analysis of Bird Vocalizations
Machine Learning-Based Scheduling in Steel Manufacturing
Prediction of compound-target interactions of natural products using large-scale drug and protein information
Deep learning-based lightweight radar target detection method
Machine learning-based quantitative prediction of drug exposure in drug-drug interactions using drug label information
Machine Learning–Based Identification of Target Groups for Thrombectomy in Acute Stroke
A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles
Users & Machine Learning-based Curation Systems
Machine learning-based available bandwidth estimation
Machine learning-based test smell detection
WorMachine: machine learning-based phenotypic analysis tool for worms
Supervised machine learning-based Hall thruster scaling
Machine Learning-Based Analysis of Bird Vocalizations
Machine Learning-Based Scheduling in Steel Manufacturing
Prediction of compound-target interactions of natural products using large-scale drug and protein information
Deep learning-based lightweight radar target detection method