Author

Mehdi Yazdani-Jahromi

University of Central FloridaORCID 0000-0001-6658-6591Unclaimed 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:protein structure· 2 Research Focus:benchmarking· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Aida Tayebi· 2 shared Craig J. NealiD· 2 shared Elayaraja KolanthaiiD· 2 shared Niloofar YousefiiD· 2 shared Özlem Özmen GaribayiD· 2 shared Sudipta SealiD· 2 shared Agnivo GosaiiD· 1 shared Ganesh BalasubramanianiD· 1 shared

Activity by Year

2022-2023 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 36 mutual co-author links

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2 shared papersBioinformatics

Aida Tayebi

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2 papers

Recent·Most cited

BioinformaticsBriefings in BioinformaticsPeer-reviewedApr 24, 2023

BindingSiteAugmentedDTA: Enabling A Next-Generation Pipeline for Interpretable Prediction Models in Drug-Repurposing

Niloofar Yousefi, Mehdi Yazdani-Jahromi, Aida Tayebi…·Özlem Özmen Garibay

This paper introduces a deep learning framework for drug-target interaction prediction that improves accuracy and interpretability by incorporating binding site information and validates it through experimental testing.

28 citationstop 5%

protein structuredeep learning

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BioinformaticsBriefings in BioinformaticsPeer-reviewedJul 11, 2022

Interpretable and Generalizable Attention-Based Model for Predicting Drug-Target Interaction Using 3D Structure of Protein Binding Sites: SARS-CoV-2 Case Study and in-Lab Validation

Mehdi Yazdani-Jahromi, Niloofar Yousefi, Aida Tayebi…·Özlem Özmen Garibay

This paper introduces an interpretable graph-based deep learning model for predicting drug-target interactions using protein binding sites, validated with experimental testing on SARS-CoV-2 targets.

125 citationstop 1%

protein structuredeep learning

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