Author

Markus A. Seeliger

Stony Brook SchoolORCID 0000-0003-0990-1756Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Assay:proteomics· 2 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Andrea VolkameriD· 1 shared Aziz M. RangwalaiD· 1 shared Bert L. de GrootiD· 1 shared Clara D. ChristiD· 1 shared David SchalleriD· 1 shared Dedi WangiD· 1 shared Jenke ScheeniD· 1 shared Jessica B. WhiteiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperBiophysics

Andrea VolkamerORCID

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2 papers

Recent·Most cited

BiophysicsThe Journal of Physical Chemistry BPeer-reviewedMar 7, 2025

Prospective evaluation of structure-based simulations reveal their ability to predict the impact of kinase mutations on inhibitor binding

Sukrit Singh, Vytautas Gapsys, Matteo Aldeghi…·John D. Chodera

The paper evaluates structure-based methods to predict how kinase mutations affect inhibitor binding, finding they accurately classify mutations as resistant or sensitizing.

16 citationstop 2%

humanproteomics

𝕏 PostBluesky

BiophysicsJournal of Chemical Theory and ComputationPeer-reviewedJul 11, 2024

Calculating Protein-Ligand Residence Times Through State Predictive Information Bottleneck based Enhanced Sampling

Suemin Lee, Dedi Wang, Markus A. Seeliger, Pratyush Tiwary

This paper introduces a method to calculate protein-ligand residence times across wide timescales using deep learning and enhanced sampling.

33 citationstop 4%

proteomicsdeep learning

𝕏 PostBluesky