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...

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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:	Mechanism of action Cell viability Gene expression Protein Inhibitors Computational linguistics. Natural language processing P98-98.5 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/6191d80f2c78430a9578d4cda558557c
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spelling	oai:doaj.org-article:6191d80f2c78430a9578d4cda558557c2021-11-28T12:28:59ZClassification of drugs based on mechanism of action using machine learning techniques10.1007/s44163-021-00012-22731-0809https://doaj.org/article/6191d80f2c78430a9578d4cda558557c2021-11-01T00:00:00Zhttps://doi.org/10.1007/s44163-021-00012-2https://doaj.org/toc/2731-0809Abstract 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.H. L. GururajFrancesco FlamminiH. A. Chaya KumariG. R. PuneethB. R. Sunil KumarSpringerarticleMechanism of actionCell viabilityGene expressionProteinInhibitorsComputational linguistics. Natural language processingP98-98.5Electronic computers. Computer scienceQA75.5-76.95ENDiscover Artificial Intelligence, Vol 1, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mechanism of action Cell viability Gene expression Protein Inhibitors Computational linguistics. Natural language processing P98-98.5 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Mechanism of action Cell viability Gene expression Protein Inhibitors Computational linguistics. Natural language processing P98-98.5 Electronic computers. Computer science QA75.5-76.95 H. L. Gururaj Francesco Flammini H. A. Chaya Kumari G. R. Puneeth B. R. Sunil Kumar Classification of drugs based on mechanism of action using machine learning techniques
description	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.
format	article
author	H. L. Gururaj Francesco Flammini H. A. Chaya Kumari G. R. Puneeth B. R. Sunil Kumar
author_facet	H. L. Gururaj Francesco Flammini H. A. Chaya Kumari G. R. Puneeth B. R. Sunil Kumar
author_sort	H. L. Gururaj
title	Classification of drugs based on mechanism of action using machine learning techniques
title_short	Classification of drugs based on mechanism of action using machine learning techniques
title_full	Classification of drugs based on mechanism of action using machine learning techniques
title_fullStr	Classification of drugs based on mechanism of action using machine learning techniques
title_full_unstemmed	Classification of drugs based on mechanism of action using machine learning techniques
title_sort	classification of drugs based on mechanism of action using machine learning techniques
publisher	Springer
publishDate	2021
url	https://doaj.org/article/6191d80f2c78430a9578d4cda558557c
work_keys_str_mv	AT hlgururaj classificationofdrugsbasedonmechanismofactionusingmachinelearningtechniques AT francescoflammini classificationofdrugsbasedonmechanismofactionusingmachinelearningtechniques AT hachayakumari classificationofdrugsbasedonmechanismofactionusingmachinelearningtechniques AT grpuneeth classificationofdrugsbasedonmechanismofactionusingmachinelearningtechniques AT brsunilkumar classificationofdrugsbasedonmechanismofactionusingmachinelearningtechniques
_version_	1718407957062877184

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

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