Author

Hooman Yari

University of Oklahoma Health Sciences CenterORCID 0000-0002-8285-7985Unclaimed 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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Organism:human· 2 Approach:machine learning (classical)· 2 Assay:proteomics· 2 Research Focus:gene regulatory network inference· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Bjoern PetersiD· 2 shared Morten NielseniD· 2 shared Saghar KaabinejadianiD· 2 shared William H. HildebrandiD· 2 shared Alessandro SetteiD· 1 shared Carolina BarraiD· 1 shared Chloe M. ShepherdiD· 1 shared Heli M. Garcia AlvareziD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersBioinformatics

Bjoern PetersORCID

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2 papers

Recent·Most cited

NetMHCIIphosPan: a machine learning tool for predictingHLA class II antigen presentation of phosphorylated peptides.

Heli M. Garcia Alvarez, Saghar Kaabinejadian, Hooman Yari, Chloe M. Shepherd, William H. Hildebrand, Alessandro Sette, Bjoern Peters, Robert Parker, Nicola Ternette, Morten Nielsen

NetMHCIIphosPan predicts HLA class II antigen presentation of phosphorylated peptides using immunopeptidomics data, outperforming existing tools.

Journal of Proteome Research · Apr 17, 2026Peer-reviewedBioinformatics

Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome by accurate and comprehensive HLA-DQ antigen presentation prediction

Jonas Birkelund Nilsson, Saghar Kaabinejadian, Hooman Yari, Bjoern Peters, Carolina Barra, Loren A. Gragert, William H. Hildebrand, Morten Nielsen

The paper improves HLA-DQ antigen presentation prediction using machine learning and shows trans-only variants have limited impact on the immunopeptidome.

Communications Biology · Apr 21, 2023Peer-reviewedBioinformatics