Integration of Random Forest Classifiers and Deep Convolutional Neural Networks for Classification and Biomolecular Modeling of Cancer Driver Mutations

Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approache...

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Detalles Bibliográficos
Autores principales: Agajanian, Steve, Oluyemi, Odeyemi, Verkhivker, Gennady M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Molecular Biosciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6579812/
https://www.ncbi.nlm.nih.gov/pubmed/31245384
http://dx.doi.org/10.3389/fmolb.2019.00044

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6579812/
https://www.ncbi.nlm.nih.gov/pubmed/31245384
http://dx.doi.org/10.3389/fmolb.2019.00044

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