Tobias Olenyi

University of Auckland — New Zealand

Biochemistry, Genetics and Molecular Biology · Life Sciences

9h-index885citations30works3.42yr avg
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Research Topics

Machine Learning in Bioinformatics(20), Genomics and Phylogenetic Studies(13), Bioinformatics and Genomic Networks(9), Protein Structure and Dynamics(8), RNA and protein synthesis mechanisms(7)

Publications30 total

Biocentral: Embedding-based Protein Predictions
Journal of Molecular Biology·2026Open Access
<i>biocentral</i> : embedding-based protein predictions
2025Open Access
FlatProt: 2D visualization eases protein structure comparison
BMC Bioinformatics·2025Open Access
FlatProt: 2D visualization eases protein structure comparison
2025Open Access
Critical assessment of missense variant effect predictors on disease-relevant variant data
Human Genetics·2025· 17 citedOpen Access
TMVisDB: Annotation and 3D-visualization of Transmembrane Proteins
Journal of Molecular Biology·2025· 4 citedOpen Access
ProtSpace: A Tool for Visualizing Protein Space
Journal of Molecular Biology·2025· 6 citedOpen Access
biocentral: embedding-based protein predictions
SSRN Electronic Journal·2025Open Access
ProtSpace: a tool for visualizing protein space
2024· 1 citedOpen Access
TMVisDB: Annotation and 3D-visualization of transmembrane proteins
2024Open Access
Critical assessment of missense variant effect predictors on disease-relevant variant data
2024· 9 citedOpen Access
<scp>LambdaPP</scp> : Fast and accessible protein‐specific phenotype predictions
Protein Science·2022· 17 citedOpen Access
Refining Embedding-Based Binding Predictions by Leveraging AlphaFold2 Structures
2022· 2 citedOpen Access
LambdaPP: Fast and accessible protein-specific phenotype predictions
2022· 7 citedOpen Access
VESPAl Prediction of the human proteome (downloaded 22/01/17)
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
VESPAl Prediction of the human proteome (downloaded 22/01/17)
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
Embeddings from protein language models predict conservation and variant effects
Human Genetics·2021· 165 citedOpen Access
Embeddings from protein language models predict conservation and variant effects
2021· 2 citedOpen Access
Embeddings from protein language models predict conservation and variant effects
2021· 8 citedOpen Access
Embeddings from protein language models predict conservation and variant effects
Zenodo (CERN European Organization for Nuclear Research)·2021Open Access
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Frequent Co-authors

Burkhard Rost(23), Michael Heinzinger(20), Christian Dallago(16), Céline Marquet(14), Michael Bernhofer(10), Maria Littmann(8), Kyra Erckert(7), Konstantin Schütze(6), Dmitrii Nechaev(5), Milot Mirdita(4), Martin Steinegger(4), Tobias Senoner(4), Ivan Koludarov(4), Paula Schloetermann(3), Amine Smaoui(3), Luisa F. Jiménez‐Soto(3), Tim Karl(2), Venkata Satagopam(2), Jiajun Qiu(2), Guy Yachdav(2)