Author

Ahmad Salim Al-Sibahi

University of CopenhagenORCID 0000-0002-3445-2334Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:protein structure· 2 Research Focus:protein structure prediction· 2 Approach:Bayesian inference· 1 Approach:deep learning· 1

Frequent Co-Authors

Lys Sanz MoretaiD· 2 shared Thomas HamelryckiD· 2 shared Anders B. Sørensen· 1 shared Andreas Manoukian· 1 shared Basile RommesiD· 1 shared Christian Bahne ThygeseniD· 1 shared Christian S. SteenmannsiD· 1 shared Douglas L. TheobaldiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

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2 shared papersBioinformatics

Lys Sanz MoretaORCID

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2 papers

Recent·Most cited

Efficient Generative Modelling of Protein Structure Fragments using a Deep Markov Model

Christian Bahne Thygesen, Ahmad Salim Al-Sibahi, Christian S. Steenmanns, Lys Sanz Moreta, Anders B. Sørensen, Thomas Hamelryck

BIFROST generates high-quality protein structure fragments using a Deep Markov Model, faster and with less input than current methods.

bioRxiv · Jun 22, 2021 · PreprintBioinformatics

A Probabilistic Programming Approach to Protein Structure Superposition

Lys Sanz Moreta, Ahmad Salim Al-Sibahi, Douglas L. Theobald, William Bullock, Basile Rommes, Andreas Manoukian, Thomas Hamelryck

This paper introduces THESEUS-PP, a probabilistic programming approach for protein structure superposition that uses Bayesian models to account for correlated atom positions and heteroscedasticity.

IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) · Jul 1, 2019Peer-reviewedBioinformatics