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Supervised learning methods in modeling of CD4+ T cell heterogeneity
Pinyi Lu
,
Vida Abedi
, Yongguo Mei
, Raquel Hontecillas
, Stefan Hoops
, Adria Carbo
, Josep Bassaganya-Riera
Department of Public Health Sciences
Research output
:
Contribution to journal
›
Article
›
peer-review
16
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Scopus citations
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Dive into the research topics of 'Supervised learning methods in modeling of CD4+ T cell heterogeneity'. Together they form a unique fingerprint.
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Keyphrases
Artificial Neural Network
100%
Random Forest
100%
CD4+ T
100%
Cellular Heterogeneity
100%
Supervised Learning Method
100%
Immune System
80%
Intracellular Signaling
40%
Ordinary Differential Equations
40%
Equation-based
40%
Linear Regression
20%
Least Squares Support Vector Regression (LSSVR)
20%
Cell Differentiation
20%
Dynamic Behavior
20%
Molecular Mechanism
20%
Machine Learning
20%
Cell-to-cell
20%
Model Prediction
20%
Macrophages
20%
Prediction Method
20%
Highly Nonlinear
20%
Neutrophils
20%
Dendritic Cells
20%
T Cells
20%
Complex Interplay
20%
Eosinophils
20%
Modeling Framework
20%
Computational Complexity
20%
B Cells
20%
Data Analytics
20%
Unique Functions
20%
Treg
20%
T Helper 17 (Th17)
20%
CD4+ T Cells
20%
Computational Systems Biology
20%
Th1-Th2
20%
Overlap Function
20%
Biochemical Reactions
20%
Systems Biology Approach
20%
Cytokine Concentration
20%
Training Model
20%
Background Modeling
20%
Signal Model
20%
Building Complex
20%
Related Entity
20%
Heterogeneous Cell Population
20%
Applications of Supervised Learning
20%
Biochemistry, Genetics and Molecular Biology
T Cell
100%
CD4
100%
Random Forest
100%
Cell Heterogeneity
100%
Artificial Neural Network
100%
Immunity
80%
Cellular Differentiation
40%
Cytokine
20%
Macrophage
20%
Intracellular Signaling
20%
B Cell
20%
Support Vector Machine
20%
Dendritic Cell
20%
Regulatory T Cell
20%
Complex System
20%
Computational Systems Biology
20%
Medicine and Dentistry
T-Helper Cell
100%
Immune System
100%
Linear Regression Analysis
25%
T Cell
25%
Intracellular Signaling
25%
Cytokine
25%
In Silico
25%
Cell Differentiation
25%
Macrophage
25%
Dendritic Cell
25%
B Cell
25%
Cell Population
25%
T Cell Differentiation
25%
Neutrophil
25%
Eosinophil
25%
Neuroscience
T Cell
100%
Neural Network
100%
CD4
100%
Cellular Differentiation
40%
Behavior (Neuroscience)
20%
B Cell
20%
Intracellular Signaling
20%
Macrophage
20%
Support Vector Machine
20%
Chemical Engineering
Supervised Learning
100%
Neural Network
100%
Learning System
20%
Support Vector Machine
20%