Author

Madeline M. Diep

Fraunhofer USAORCID 0000-0002-9908-0367Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:software / tool· 2 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Advait BalajiiD· 1 shared Aleksandr Smirnov· 1 shared Anthony D. KappelliD· 1 shared Bryce L. KilleiD· 1 shared Daniel J. NaskoiD· 1 shared Dreycey AlbiniD· 1 shared Gene D. GodboldiD· 1 shared Gudjon Magnusson· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Advait BalajiORCID

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2 papers

Recent·Most cited

NeuroWRAP: integrating, validating, and sharing neurodata analysis workflows

Zac Bowen, Gudjon Magnusson, Madeline M. Diep, Ujjwal Ayyangar, Aleksandr Smirnov, Patrick O. Kanold, Wolfgang Losert

NeuroWRAP integrates and evaluates multiphoton calcium imaging analysis workflows to improve reproducibility and collaboration by combining existing algorithms and enabling custom workflows.

Frontiers in Neuroinformatics · Apr 25, 2023Peer-reviewedNeuroscience

SeqScreen: Accurate and Sensitive Functional Screening of Pathogenic Sequences via Ensemble Learning

Advait Balaji, Bryce L. Kille, Anthony D. Kappell, Gene D. Godbold, Madeline M. Diep, Ryan A. Leo Elworth, Zhiqin Qian, Dreycey Albin, Daniel J. Nasko, Nidhi Shah, Mihai Pop, Santiago Segarra, Krista L. Ternus, Todd J. Treangen

SeqScreen uses ensemble learning to accurately label pathogenic sequences with functional annotations, achieving high recall and precision for microbial pathogenesis.

Genome biology · Jun 20, 2022Peer-reviewedBioinformatics