Author

Sungho Shin

University of Wisconsin–MadisonORCID 0000-0002-9889-3278Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Organism:human· 1 Approach:statistical model· 1

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Ophelia S. VenturelliiD· 1 shared Víctor M. ZavalaiD· 1 shared

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2019-2019 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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1 shared paperBioinformatics

Ophelia S. VenturelliORCID

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1 paper

Recent·Most cited

BioinformaticsPLoS Computational BiologyPeer-reviewedMar 25, 2019

Scalable Nonlinear Programming Framework for Parameter Estimation in Dynamic Biological System Models

Sungho Shin, Ophelia S. Venturelli, Víctor M. Zavala

The paper introduces a scalable nonlinear programming framework for parameter estimation in dynamic biological models, demonstrating its efficiency on large-scale synthetic microbiome data.

27 citations

humanstatistical model

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