Using Supervised Learning Methods for Gene Selection in RNA-Seq Case-Control Studies-Reference-Cited by-同舟云学术

Using Supervised Learning Methods for Gene Selection in RNA-Seq Case-Control Studies

Published:2018-08-03 Issue: Volume:9 Page:
ISSN:1664-8021
Container-title:Frontiers in Genetics
language:
Short-container-title:Front. Genet.

Author:

Wenric Stephane,Shemirani Ruhollah

Publisher

Frontiers Media SA

Subject

Genetics(clinical),Genetics,Molecular Medicine

Reference38 articles.

1. A balanced iterative random forest for gene selection from microarray data;Anaissi;BMC Bioinformatics,2013

2. The IGF-1 receptor in cancer biology;Baserga;Int. J. Cancer,2003

3. Epidermal growth factor receptor and HER2-neu mRNA expression in non-small cell lung cancer is correlated with survival;Brabender;Clin. Cancer Res.,2001

4. The IGF hormonal network in endometrial cancer: functions, regulation, and targeting approaches;Bruchim;Front. Endocrinol.,2014

5. Prediagnostic plasma IGFBP-1, IGF-1 and risk of prostate cancer;Cao;Int. J. Cancer,2015

Cited by 37 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Differential gene expression analysis pipelines and bioinformatic tools for the identification of specific biomarkers: A review;Computational and Structural Biotechnology Journal;2024-12

2. AITeQ: a machine learning framework for Alzheimer’s prediction using a distinctive five-gene signature;Briefings in Bioinformatics;2024-05-23

3. From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies;Molecular Biotechnology;2024-04-02

4. AITeQ: A machine learning framework for Alzheimer’s prediction using a distinctive 5-gene signature;2023-09-18

5. Mapping disease regulatory circuits at cell-type resolution from single-cell multiomics data;Nature Computational Science;2023-07-25