Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering

Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering

The type-IV bacterial pili and multiheme c-type cytochrome protein family have gained significant attention due to their role in extracellular electron transfer (EET), which defines their electrogenic properties. These electrogenic behaviors play a crucial role in interspecies microbial communicatio...

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Bibliographic Details
Main Authors: Dheeraj Raya, Vincent Peta, Alain Bomgni, Shiva Aryal, Tuyen Duc Do, Kalimuthu Jawaharraj, David R. Salem, Venkataramana Gadhamshetty, Saurabh Sudha Dhiman, Etienne Z. Gnimpieba
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Computational and Structural Biotechnology Journal
Subjects:
Bacterial nanowires
Biofilm
Biologically informed neural network
Gene ontology
Machine learning
Protein sequence-based prediction
Online Access:http://www.sciencedirect.com/science/article/pii/S2001037025001436
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