Author

Tuyen Do

University of South DakotaORCID 0000-0002-1817-4565Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Assay:protein sequence· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Etienne Z. GnimpiébaiD· 2 shared Alain Bertrand BomgniiD· 1 shared Bichar Dip Shrestha GurungiD· 1 shared David R. SalemiD· 1 shared Dheeraj RayaiD· 1 shared Dikshya BhandariiD· 1 shared Kalimuthu JawaharrajiD· 1 shared Manish RayamajhiiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Etienne Z. GnimpiébaORCID

Mutual co-authors in cluster

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2 papers

Recent·Most cited

Forecasting Urban Wastewater Microbiome Dynamics Using a Digital Twin Framework

Bichar Dip Shrestha Gurung, Manish Rayamajhi, Naina Maharjan, Tuyen Do, Dikshya Bhandari, Rupesh Yadav, Shiva Aryal, Etienne Z. Gnimpiéba

This paper introduces a digital twin framework using Q-net to forecast microbial abundance in urban wastewater, achieving high accuracy in temporal dynamics and enabling scenario simulations.

bioRxiv · Jul 21, 2025 · PreprintBioinformatics

Classification of bacterial nanowire proteins using Machine Learning and Feature Engineering model

Dheeraj Raya, Vincent Peta, Alain Bertrand Bomgni, Tuyen Do, Kalimuthu Jawaharraj, David R. Salem, Venkataramana R. Gadhamshetty, Etienne Z. Gnimpiéba, Saurabh Sudha Dhiman

The paper develops a machine learning model to classify bacterial nanowire proteins using feature engineering, achieving high accuracy with XGBoost.

bioRxiv · May 3, 2023 · PreprintSystems Biology