Classification of drugs based on mechanism of action using machine learning techniques

Abstract The mechanism of action is an important aspect of drug development. It can help scientists in the process of drug discovery. This paper provides a machine learning model to predict the mechanism of action of a drug. The machine learning models used in this paper are Binary Relevance K Neare...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: H. L. Gururaj, Francesco Flammini, H. A. Chaya Kumari, G. R. Puneeth, B. R. Sunil Kumar
Formato: article
Lenguaje:EN
Publicado: Springer 2021
Materias:
Acceso en línea:https://doaj.org/article/6191d80f2c78430a9578d4cda558557c
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Abstract The mechanism of action is an important aspect of drug development. It can help scientists in the process of drug discovery. This paper provides a machine learning model to predict the mechanism of action of a drug. The machine learning models used in this paper are Binary Relevance K Nearest Neighbors (Type A and Type B), Multi-label K-Nearest Neighbors and a custom neural network. These machine learning models are evaluated using the mean column-wise log loss. The custom neural network model had the best accuracy with a log loss of 0.01706. This neural network model is integrated into a web application using Flask framework. A user can upload a custom testing features dataset, which contains the gene expression and the cell viability levels. The web application will output the top classes of drugs, along with the scatter plots for each of the drug.