An Efficient Dilated DTCN with Residual LSTM-based Allergenicity Prediction for Chemical Compounds using Optimal Weighted Feature Selection and Improved Optimization Mechanism-Reference-Cited by-同舟云学术

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An Efficient Dilated DTCN with Residual LSTM-based Allergenicity Prediction for Chemical Compounds using Optimal Weighted Feature Selection and Improved Optimization Mechanism

Published:2024-04-02 Issue: Volume:15(9) Page:1-17
ISSN:
Container-title:2024 2nd International Conference on Networking and Communications (ICNWC)
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Author:

Padmavathy T.¹,Thenmozhi M.²,Madhavan Thirumurthy³

Affiliation:

1. SRM Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,India

2. SRM Institute of Science and Technology,Department of Networking and Communications,Chennai,India

3. SRM Institute of Science and Technology,Department of Genetic Engineering,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10537254/10537235/10537543.pdf?arnumber=10537543

Reference34 articles.

1. ChAlPred: A web server for prediction of allergenicity of chemical compounds

2. Allergenicity prediction of novel and modified proteins: Not a mission impossible! Development of a Random Forest allergenicity prediction model

3. Prediction of Allergenic Proteins by Means of the Concept of Chou's Pseudo Amino Acid Composition and a Machine Learning Approach

4. A Comparative Analysis of Novel Deep Learning and Ensemble Learning Models to Predict the Allergenicity of Food Proteins

5. PREAL: prediction of allergenic protein by maximum Relevance Minimum Redundancy (mRMR) feature selection

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