Prediction of Inhibition Activity of Dihydrofolate Reductase Inhibitors With Multivariate Adaptive Regression Splines-Reference-Cited by-同舟云学术

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Prediction of Inhibition Activity of Dihydrofolate Reductase Inhibitors With Multivariate Adaptive Regression Splines

Published:2023 Issue: Volume:11 Page:50595-50604
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Qayyum Zanib¹^ORCID,Mehmood Tahir¹^ORCID,Al-Essa Laila A.²^ORCID

Affiliation:

1. Department of Mathematics, School of Natural Sciences, National University of Sciences and Technology (NUST), Islamabad, Pakistan

2. Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Funder

Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10113638.pdf?arnumber=10113638

Reference39 articles.

1. Application of PC-ANN and PC-LS-SVM in QSAR of CCR1 antagonist compounds: A comparative study

2. Deep learning using rectified linear units (ReLU);fred agarap;arXiv 1803 08375,2018

3. QSAR study of isonicotinamides derivatives as Alzheimr’s disease inhibitors using PLS-R and ANN methods;el aissouq;Proc Int Conf Intell Syst Adv Comput Sci (ISACS),2019

4. A logical calculus of the ideas immanent in nervous activity

5. Shuffling multivariate adaptive regression splines and adaptive neuro-fuzzy inference system as tools for QSAR study of SARS inhibitors

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