NDLI: Prediction of drug synergy score using ensemble based differential evolution

Content Provider	IET Digital Library
Author	Singh, Harpreet Rana, Prashant Singh Singh, Urvinder
Abstract	Prediction of drug synergy score is an ill-posed problem. It plays an efficient role in the medical field for inhibiting specific cancer agents. An efficient regression-based machine learning technique has an ability to minimise the drug synergy prediction errors. Therefore, in this study, an efficient machine learning technique for drug synergy prediction technique is designed by using ensemble based differential evolution (DE) for optimising the support vector machine (SVM). Because the tuning of the attributes of SVM kernel regulates the prediction precision. The ensemble based DE employs two trial vector generation techniques and two control attributes settings. The initial generation technique has the best solution and the other is without the best solution. The proposed and existing competitive machine learning techniques are applied to drug synergy data. The extensive analysis demonstrates that the proposed technique outperforms others in terms of accuracy, root mean square error and coefficient of correlation.
Starting Page	24
Ending Page	29
Page Count	6
ISSN	17518849
Volume Number	13
e-ISSN	17518857
Issue Number	Issue 1, Feb (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-syb/13/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-syb.2018.5023
Journal	IET Systems Biology
Publisher Date	2018-09-25
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Cancer Competitive Machine Learning Technique Control Attribute Settings Drug Synergy Data Drug Synergy Prediction Error Drug Synergy Prediction Technique Drug Synergy Score Prediction Drugs Efficient Machine Learning Technique Efficient Regression-based Machine Learning Technique Ensemble Based DE Ensemble Based Differential Evolution Evolutionary Computation Initial Generation Technique Knowledge Engineering Technique Learning in AI Medical Computing Medical Field Optimisation Technique Prediction Precision Regression Analysis Root Mean Square Error Specific Cancer Agent Statistics Support Vector Machine SVM Kernel Attributes Trial Vector Generation Technique
Content Type	Text
Resource Type	Article
Subject	Cell Biology Genetics Molecular Biology Modeling and Simulation Biotechnology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Efficient prediction of drug–drug interaction using deep learning models

Ensembled machine learning framework for drug sensitivity prediction

State of charge prediction for UAVs based on support vector machine

A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier

Randomised learning-based hybrid ensemble model for probabilistic forecasting of PV power generation

Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification

Lung cancer prediction from microarray data by gene expression programming

States prediction for solar power and wind speed using BBA-SVM

Acceleration for proximal stochastic dual coordinate ascent algorithm in solving regularised loss minimisation with ℓ2norm

Prediction of drug synergy score using ensemble based differential evolution

Similar Documents

Efficient prediction of drug–drug interaction using deep learning models

Ensembled machine learning framework for drug sensitivity prediction

State of charge prediction for UAVs based on support vector machine

A Hierarchical Method for Transient Stability Prediction of Power Systems Using the Confidence of a SVM-Based Ensemble Classifier

Randomised learning-based hybrid ensemble model for probabilistic forecasting of PV power generation

Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification

Lung cancer prediction from microarray data by gene expression programming

States prediction for solar power and wind speed using BBA-SVM

Acceleration for proximal stochastic dual coordinate ascent algorithm in solving regularised loss minimisation with ℓ2norm

Prediction of drug synergy score using ensemble based differential evolution