Author

Ali Reza Ibrahimzada

University of Illinois Urbana-ChampaignORCID 0000-0002-3797-818XUnclaimed 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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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:DNA methylation· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Ali CakmakiD· 2 shared Huzeyfe AyaziD· 2 shared Arta ArmaniiD· 1 shared Bulent Ozpolat· 1 shared Elif Karlık· 1 shared Gihad N. Sohsah· 1 shared Guleser Demir· 1 shared Mehmet Erdem Buyukbingol· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 30 mutual co-author links

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2 shared papersBioinformatics

Ali CakmakORCID

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2 papers

Recent·Most cited

Predicting Future SARS-CoV-2 Mutations using Deep Learning

Huzeyfe Ayaz, Ali Reza Ibrahimzada, Arta Armani, Mehmet Selman Baysan, Mehmet Erdem Buyukbingol, Guleser Demir, Elif Karlık, Bulent Ozpolat, Ali Cakmak

This paper proposes deep-learning-based methods to predict future SARS-CoV-2 mutations using genomic, biochemical, and phylogenetic features, achieving an F1-Macro score of 0.78 on GISAID data.

bioRxiv · Jul 12, 2025 · PreprintBioinformatics

Scalable Classification of Organisms into a Taxonomy Using Hierarchical Supervised Learners

Gihad N. Sohsah, Ali Reza Ibrahimzada, Huzeyfe Ayaz, Ali Cakmak

The paper introduces a hierarchical classifier framework for DNA sequence taxonomy classification, showing improved accuracy and scalability compared to non-hierarchical methods.

Journal of Bioinformatics and Computational Biology · Jun 12, 2020Peer-reviewedBioinformatics