6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
1 Online-Ressource.
- Language
-
Englisch
- Bibliographic citation
-
6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site ; volume:16 ; number:1 ; day:27 ; month:11 ; year:2023 ; pages:1-15 ; date:12.2023
BioData Mining ; 16, Heft 1 (27.11.2023), 1-15, 12.2023
- Creator
-
Huang, Guohua
Huang, Xiaohong
Luo, Wei
- Contributor
-
SpringerLink (Online service)
- DOI
-
10.1186/s13040-023-00348-8
- URN
-
urn:nbn:de:101:1-2024021413301487474652
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:33 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Huang, Guohua
- Huang, Xiaohong
- Luo, Wei
- SpringerLink (Online service)
Other Objects (12)
Visual element recognition based on profile coefficient and image processing technology
Visual analytics of geo-social interaction patterns for epidemic control
Enhanced Two-Step Virtual Catchment Area (E2SVCA) model to measure telehealth accessibility
Development of wellbore compound blockage removal technology to reduce production loss in the ultra-deep and high-sulfur Yuanba gas field
Stacking, blending & reclaiming
Molecular Stacking on Graphene
Molecular Stacking on Graphene
Molecular Stacking on Graphene
EMDL_m6Am: identifying N6,2′-O-dimethyladenosine sites based on stacking ensemble deep learning
Study of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells under Different Stress Conditions
Recent Progress in Microfiber-Optic Sensors
Strong Optical Excitation and High Thermoelectric Performance in 2D Holey‐Phosphorene Monolayer
Visual element recognition based on profile coefficient and image processing technology
Visual analytics of geo-social interaction patterns for epidemic control
Enhanced Two-Step Virtual Catchment Area (E2SVCA) model to measure telehealth accessibility
Development of wellbore compound blockage removal technology to reduce production loss in the ultra-deep and high-sulfur Yuanba gas field
Stacking, blending & reclaiming
Molecular Stacking on Graphene
Molecular Stacking on Graphene
Molecular Stacking on Graphene
EMDL_m6Am: identifying N6,2′-O-dimethyladenosine sites based on stacking ensemble deep learning
Study of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells under Different Stress Conditions
Recent Progress in Microfiber-Optic Sensors
Strong Optical Excitation and High Thermoelectric Performance in 2D Holey‐Phosphorene Monolayer
Visual element recognition based on profile coefficient and image processing technology
Visual analytics of geo-social interaction patterns for epidemic control
Enhanced Two-Step Virtual Catchment Area (E2SVCA) model to measure telehealth accessibility
Development of wellbore compound blockage removal technology to reduce production loss in the ultra-deep and high-sulfur Yuanba gas field
Stacking, blending & reclaiming
Molecular Stacking on Graphene
Molecular Stacking on Graphene
Molecular Stacking on Graphene
EMDL_m6Am: identifying N6,2′-O-dimethyladenosine sites based on stacking ensemble deep learning
Study of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells under Different Stress Conditions
Recent Progress in Microfiber-Optic Sensors