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StackTHPred: Identifying Tumor-Homing Peptides through GBDT-Based Feature Selection with Stacking Ensemble Architecture
Jiahui Guan, Lantian Yao, Chia Ru Chung, Ying Chih Chiang
*
,
Tzong Yi Lee
*
*
此作品的通信作者
生物資訊及系統生物研究所
國立陽明交通大學
研究成果
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同行評審
8
引文 斯高帕斯(Scopus)
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Keyphrases
Feature Selection
100%
Stacking Ensemble
100%
Ensemble Architecture
100%
Tumor-homing Peptide
100%
Cancer Therapy
25%
Matthews Correlation Coefficient
25%
Tumor Tissue
12%
Stacked Architecture
12%
Machine Learning Algorithms
12%
Computational Methods
12%
In Cancer
12%
Target Specificity
12%
Prediction Method
12%
Promising Solutions
12%
Feature Selection Methods
12%
Anticancer Drugs
12%
Intrinsic Attributes
12%
Incorporation Rate
12%
Safety Profile
12%
Machine Learning Based
12%
Learning-based Framework
12%
Oligopeptides
12%
Optimal Feature Selection
12%
Small Dataset
12%
Antigenicity
12%
Complex Time
12%
Effective Features Selection
12%
Healthy Tissue
12%
Phage Display
12%
Novel Machine
12%
Biological Safety
12%
In Vivo Screening
12%
Peptide Prediction
12%
Tree-based Machine Learning
12%
Advanced Performance
12%
Computer Science
Feature Selection
100%
Feature Extraction
100%
Matthews Correlation Coefficient
100%
Machine Learning Algorithm
50%
Interpretability
50%
Computational Method
50%
Machine Learning
50%
Learning System
50%
Biochemistry, Genetics and Molecular Biology
Feature Extraction
100%
Solution and Solubility
50%
Anticancer
50%
Target Cell
50%
Antigenicity
50%
Phage Display
50%
Oligopeptide
50%
Immunology and Microbiology
Feature Extraction
100%
Peptides
100%
Solution and Solubility
12%
Antigenicity
12%
Target Cell
12%
Phage Display
12%
Oligopeptide
12%
Material Science
Tumor
100%
Oligopeptide
11%
Phage Display
11%