Author

Suraiya Akhter

Washington State University Tri-CitiesORCID 0000-0001-6577-2034Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Research Focus:software / tool· 1

Frequent Co-Authors

John Holmes MilleriD· 1 shared John Miller· 1 shared

Activity by Year

2022-2025 · peak 1/yr

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2 top collaborators · 0 mutual co-author links

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1 shared paperBioinformatics

John Holmes MillerORCID

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2 papers

Recent·Most cited

BioinformaticsFrontiers in BioinformaticsPeer-reviewedNov 25, 2025

Bacteriocin Prediction Through Cross-Validation-Based and Hypergraph-Based Feature Evaluation Approaches

Suraiya Akhter, John Holmes Miller

The paper develops a computational model to predict bacteriocins using XGBoost with feature selection via cross-validation and hypergraph-based methods, achieving high accuracy.

DOI 10.3389/fbinf.2025.1694009

protein sequencemachine learning (classical)

𝕏 PostBluesky

BioinformaticsbioRxivPreprintSep 29, 2022

Optimal feature selection and software tool development for bacteriocin prediction

Suraiya Akhter, John Miller

This work identifies optimal features and develops a machine learning tool for predicting bacteriocin sequences with high accuracy.

2 citations

protein sequencemachine learning (classical)

𝕏 PostBluesky