Author

Farzad Jalali‐Yazdi

University of Southern CaliforniaORCID 0000-0002-0291-3482Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Colin M. LeafiD· 1 shared Justin N. OngiD· 1 shared Pearl QiiD· 1 shared Rajiv K. KaliaiD· 1 shared Richard W. RobertsiD· 1 shared Terry T. TakahashiiD· 1 shared Yash GandhiiD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperBioengineering

Colin M. LeafORCID

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1 paper

Recent·Most cited

Integrating Diffusion and Liquid AI Models for Predicting Peptide Affinity from mRNA Display Selections

Colin M. Leaf, Pearl Qi, Yash Gandhi, Farzad Jalali‐Yazdi, Justin N. Ong, Terry T. Takahashi, Rajiv K. Kalia, Richard W. Roberts

The paper predicts peptide binding affinities using machine learning models trained on mRNA display data, identifying high-affinity peptides with single-digit picomolar affinities.

bioRxiv · May 11, 2026 · PreprintBioengineering

Farzad Jalali‐Yazdi · henhao