Author

B. A. Pataki

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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Bioengineering· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Assay:behavioral assay· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Organism:E. coli· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

A. Chen· 1 shared B. C. L. van der Putten· 1 shared C. Espino· 1 shared C. McDaniel· 1 shared C. Schultsz· 1 shared COMPARE ML-AMR group· 1 shared D. Aytan-Aktug· 1 shared D. Brunner· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioengineering

A. Chen

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Author profile →

2 papers

Recent·Most cited

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

B. A. Pataki, S. Matamoros, B. C. L. van der Putten, D. Remondini, E. Giampieri, D. Aytan-Aktug, R. S. Hendriksen, O. Lund, I. Csabai, C. Schultsz, COMPARE ML-AMR group

This paper predicts ciprofloxacin minimum inhibitory concentration in Escherichia coli using machine learning based on genome-wide mutation profiles and antimicrobial resistance gene presence.

bioRxiv · Jan 17, 2020Microbiology

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge

S. K. Sieberts, J. Schaff, M. Duda, B. A. Pataki, M. Sun, P. Snyder, J.-F. Daneault, F. Parisi, G. Costante, U. Rubin, P. Banda, Y. Chae, E. C. Neto, R. Dorsey, Z. Aydın, , Omberg

The paper evaluates digital biomarkers from wearable data to predict Parkinson's disease status and symptom severity using a crowdsourced challenge.

bioRxiv · Jan 13, 2020Bioengineering