Evaluating the performance of random forest and iterative random forest based methods when applied to gene expression data

Evaluating the performance of random forest and iterative random forest based methods when applied to gene expression data

Gene-to-gene networks, such as Gene Regulatory Networks (GRN) and Predictive Expression Networks (PEN) capture relationships between genes and are beneficial for use in downstream biological analyses. There exists multiple network inference tools to produce these gene-to-gene networks from matrices...

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Bibliographic Details
Main Authors: Angelica M. Walker, Ashley Cliff, Jonathon Romero, Manesh B. Shah, Piet Jones, Joao Gabriel Felipe Machado Gazolla, Daniel A Jacobson, David Kainer
Format: Article
Language:English
Published: Elsevier 2022-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Random forest
Iterative random forest
Gene expression networks
Network biology
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037022002513

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http://www.sciencedirect.com/science/article/pii/S2001037022002513

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