Deep-CABPred: Deep learning model for predicting functional chlorophyll a-b binding proteins in trait-based plant ecology using hybrid embedding with semi-normalized temporal convolutional networks

Chlorophyll a-b binding proteins (CABs) are crucial for photosynthesis, directly influencing plant efficiency and environmental adaptation. Identifying these proteins is vital for understanding ecological function and productivity, but traditional experimental methods are laborious. To overcome this...

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Bibliographic Details

Published in:	Ecological Informatics
Main Authors:	Farman Ali, Raed Alsini, Tamim Alkhalifah, Fahad Alturise, Wajdi Alghamdi, Majdi Khalid
Format:	Article
Language:	English
Published:	Elsevier 2025-11-01
Subjects:	Chlorophyll a-b binding proteins Deep learning Machine learning Semi-normalized temporal convolutional network
Online Access:	http://www.sciencedirect.com/science/article/pii/S1574954125004091