scholarly journals Gene Selection for Microarray Cancer Data Classification by a Novel Rule-Based Algorithm

Information ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Adrian Pino Angulo
Keyword(s):  
Gene Selection ◽  
Data Classification ◽  
Rule Based ◽  
Cancer Data ◽  
Selection For

Gene selection for microarray data classification via adaptive hypergraph embedded dictionary learning

Gene ◽  
2019 ◽  
Vol 706 ◽  
pp. 188-200 ◽  
Author(s):  
Xiao Zheng ◽  
Wenyang Zhu ◽  
Chang Tang ◽  
Minhui Wang
Keyword(s):  
Microarray Data ◽  
Dictionary Learning ◽  
Gene Selection ◽  
Data Classification ◽  
Selection For

Improving PLS–RFE based gene selection for microarray data classification

2015 ◽  
Vol 62 ◽  
pp. 14-24 ◽  
Author(s):  
Aiguo Wang ◽  
Ning An ◽  
Guilin Chen ◽  
Lian Li ◽  
Gil Alterovitz
Keyword(s):  
Microarray Data ◽  
Gene Selection ◽  
Data Classification ◽  
Selection For

Gene selection for microarray data classification based on Grey Wolf Optimizer enhanced with TRIZ-inspired operators

2021 ◽  
pp. 107034
Author(s):  
Osama Ahmad Alomari ◽  
Sharif Naser Makhadmeh ◽  
Mohammed Azmi Al-Betar ◽  
Zaid Abdi Alkareem Alyasseri ◽  
Iyad Abu Doush ◽  
...  
Keyword(s):  
Microarray Data ◽  
Gene Selection ◽  
Data Classification ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Selection For

scholarly journals Gene selection for microarray data classification via multi-objective graph theoretic-based method

2022 ◽  
Vol 123 ◽  
pp. 102228
Author(s):  
Mehrdad Rostami ◽  
Saman Forouzandeh ◽  
Kamal Berahmand ◽  
Mina Soltani ◽  
Meisam Shahsavari ◽  
...  
Keyword(s):  
Microarray Data ◽  
Gene Selection ◽  
Data Classification ◽  
Multi Objective ◽  
Graph Theoretic ◽  
Selection For

scholarly journals Gene selection for survival data under dependent censoring: A copula-based approach

2016 ◽  
Vol 25 (6) ◽  
pp. 2840-2857 ◽  
Author(s):  
Takeshi Emura ◽  
Yi-Hau Chen
Keyword(s):  
Survival Data ◽  
Gene Selection ◽  
Cox Regression ◽  
Selection Procedure ◽  
Dependent Censoring ◽  
Small Cell Lung ◽  
Gene Expressions ◽  
Cancer Data ◽  
Independent Censoring ◽  
Selection For

Dependent censoring arises in biomedical studies when the survival outcome of interest is censored by competing risks. In survival data with microarray gene expressions, gene selection based on the univariate Cox regression analyses has been used extensively in medical research, which however, is only valid under the independent censoring assumption. In this paper, we first consider a copula-based framework to investigate the bias caused by dependent censoring on gene selection. Then, we utilize the copula-based dependence model to develop an alternative gene selection procedure. Simulations show that the proposed procedure adjusts for the effect of dependent censoring and thus outperforms the existing method when dependent censoring is indeed present. The non-small-cell lung cancer data are analyzed to demonstrate the usefulness of our proposal. We implemented the proposed method in an R “compound.Cox” package.

Sign in / Sign up

Export Citation Format

Share Document