Author

Dominic Pühringer

University of ViennaORCID 0000-0001-5812-9585Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 1 Approach:machine learning (classical)· 1 Assay:proteomics· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Georg MlynekiD· 1 shared Július KošťaniD· 1 shared Kristina Djinović‐CarugoiD· 1 shared Luís Rocha LopesiD· 1 shared Luke J. Smith· 1 shared Mathias GauteliD· 1 shared Michael NagyiD· 1 shared Mohammed Majid AkhtariD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBiophysics

Georg MlynekORCID

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1 paper

Recent·Most cited

BiophysicsbioRxivPreprintAug 5, 2023

Unlocking Predictive Power: A Machine Learning Tool Derived from In-Depth Analysis to Forecast the Impact of Missense Variants in Human Filamin C

Michael Nagy, Georg Mlynek, Július Košťan…·Kristina Djinović‐Carugo

The paper develops a machine learning model to predict the impact of missense variants in human filamin C, achieving high accuracy in distinguishing pathogenic from non-pathogenic variants.

3 citations

humanproteomics

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