A robust and stable gene selection algorithm based on graph theory and machine learning

Saha, S., Soliman, A., & Rajasekaran, S. (2021). A robust and stable gene selection algorithm based on graph theory and machine learning. Human Genomics, 15(1). https://doi.org/10.1186/s40246-021-00366-9
Authors:
Subrata Saha
Ahmed Soliman
Sanguthevar Rajasekaran
Affiliated Authors:
Subrata Saha
Subjects:
Microarray Data Analysis and Gene Expression Profiling (OpenAlex Topic)
Analysis of Gene Interaction Networks (OpenAlex Topic)
Prediction of Protein Subcellular Localization (OpenAlex Topic)
Algorithms (MeSH)
Machine Learning (MeSH)
Author Keywords:
robust and stable gene selection algorithm (rsgsa)
symmetric uncertainty (su)
gain ratio (gr)
support vector machine-recursive feature elimination (svm-rfe)
linear support vector machine (lsvm)
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Publication Type:
Article
Unique ID:
10.1186/s40246-021-00366-9
PMID:
34753514
DOI:
10.1186/s40246-021-00366-9
Journal:
Human Genomics
Publication Date:
Data Source:
PubMed
Source Link:
View PubMed Record
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Record Created: