Author

A. Roder

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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Biophysics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:metagenomics· 1

Frequent Co-Authors

E. Ghedin· 2 shared A. Kreitman· 1 shared B. Wang· 1 shared C. Mederos· 1 shared D. Gresham· 1 shared D. Ruchnewitz· 1 shared H. Liu· 1 shared H. Lu· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBiophysics

E. Ghedin

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Accurate Virus Identification with Interpretable Raman Signatures by Machine Learning

J. Ye, Y.-T. Yeh, Y. Xue, Z. Wang, N. Zhang, H. Liu, K. Zhang, Z. Yu, A. Roder, N. P. Lopez, L. Organtini, W. Greene, S. Hafenstein, H. Lu, E. Ghedin, , S. X. Huang

This paper develops a machine learning model using Raman spectroscopy to accurately identify viruses, achieving high accuracy in classifying virus types and subtypes.

bioRxiv · Jun 4, 2021Biophysics

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data

A. Roder, K. E. Johnson, M. Knoll, M. Khalfan, B. Wang, S. Schultz-Cherry, S. Banakis, A. Kreitman, C. Mederos, J.-H. Youn, R. Mercado, W. Wang, D. Ruchnewitz, M. I. Samanovic, M. J. Mulligan, , E. Ghedin

This study evaluates variant calling tools for detecting minority variants in viral sequencing data and provides guidance for accurate quantification of intrahost viral diversity.

bioRxiv · May 5, 2021 · PreprintMicrobiology