Author

Luke J. Smith

King's College London

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Biophysics· 1

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

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Dominic PühringeriD· 1 shared Georg MlynekiD· 1 shared Július KošťaniD· 1 shared Kristina Djinović‐CarugoiD· 1 shared Luís Rocha LopesiD· 1 shared Mathias GauteliD· 1 shared Michael NagyiD· 1 shared Mohammed Majid AkhtariD· 1 shared

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2023-2023 · peak 1/yr

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10 top collaborators · 45 mutual co-author links

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1 shared paperBiophysics

Dominic PühringerORCID

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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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