Author

John C Papciak

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:machine learning (classical)· 2 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Organism:mouse· 1 Organism:rat· 1 Approach:statistical model· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Christopher E. MasoniD· 3 shared David DankoiD· 3 shared Dorottya Nagy‐SzakaliD· 3 shared Heather WellsiD· 3 shared Niamh B. O’HaraiD· 3 shared Gábor Fidler· 2 shared Lorenzo Uccellini· 2 shared Mara Couto-RodrigueziD· 2 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersMicrobiology

Christopher E. MasonORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2026

Gábor Fidler, Heather Wells, Patrick Ford Combs, John C Papciak, Mara Couto-Rodriguez, Sol Rey, Tiara Rivera, Lorenzo Uccellini, Christopher E. Mason, Niamh B. O’Hara, Dorottya Nagy‐Szakal, David Danko

The paper introduces BDXR, a method for antimicrobial resistance prediction, achieving high accuracy across six species-drug pairs in the CAMDA 2026 challenge.

bioRxiv · May 13, 2026 · PreprintMicrobiology

BIOTIA-DX RESISTANCE Achieved the Best Antimicrobial Resistance Phenotype Prediction Accuracy at CAMDA 2025

The paper introduces BDXR, a tool for predicting antimicrobial resistance from whole genome sequencing, achieving high accuracy in the CAMDA 2025 challenge.

bioRxiv · Sep 24, 2025 · PreprintMicrobiology

Forecasting Dengue Fever in Brazil Using Multimodal Data, Including Climate Data

David Danko, Charles J Vörösmarty, Anthony Daniel Cak, Fabio Corsi, Suraj J. Patel, John C Papciak, Heather Wells, Anthony Albanese, Christopher E. Mason, Rafael Maciel‐de‐Freitas, Dorottya Nagy‐Szakal, Niamh B. O’Hara

This paper introduces a dengue fever forecasting model for Brazil using multimodal data, achieving accurate monthly predictions up to 6 months ahead.

bioRxiv · Mar 12, 2024 · PreprintBioinformatics