A feature selection strategy for gene expression time series experiments with hidden Markov models-Reference-Cited by-同舟云学术

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A feature selection strategy for gene expression time series experiments with hidden Markov models

Published:2019-10-10 Issue:10 Volume:14 Page:e0223183
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Cárdenas-Ovando Roberto A.^ORCID,Fernández-Figueroa Edith A.^ORCID,Rueda-Zárate Héctor A.,Noguez Julieta^ORCID,Rangel-Escareño Claudia^ORCID

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference35 articles.

1. Subspace, Latent Structure and Feature Selection

2. An introduction to variable and feature selection;I Guyon;JMLR,2003

3. Computational Methods of Feature Selection

4. Supervised, Unsupervised and Semi-supervised Feature Selection: A Review on Gene Selection;JC Ang;IEEE Transactions on Computational Biology and Bioinformatics,2015

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1. A novel feature selection method using generalized inverted Dirichlet-based HMMs for image categorization;International Journal of Machine Learning and Cybernetics;2022-03-14

2. Machine Learning for Metabolic Networks Modelling: A State-of-the-Art Survey;Studies in Big Data;2022

3. Machine Learning Based Computational Gene Selection Models: A Survey, Performance Evaluation, Open Issues, and Future Research Directions;Frontiers in Genetics;2020-12-10

4. Computational discovery and modeling of novel gene expression rules encoded in the mRNA;Biochemical Society Transactions;2020-07-14

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