Author

A. Barati farimani

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Immunology· 2 Bioengineering· 1 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:drug response / drug discovery· 3 Approach:machine learning (classical)· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:mechanistic / dynamical model· 1 Assay:organoid / primary culture· 1

Frequent Co-Authors

P. Yadav· 2 shared A. Horani· 1 shared D. Stolz· 1 shared E. Jakobsson· 1 shared E. R. Jacome· 1 shared E. Tajkhorshid· 1 shared J. M. Franks· 1 shared J. Xu· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersBioengineering

P. Yadav

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Activity Map and Transition Pathways of G Protein Coupled Receptor Revealed by Machine Learning

P. Mollaei, A. Barati farimani

This study uses machine learning to predict GPCR activation states and identify transition pathways, enabling drug design targeting key amino acids.

bioRxiv · Dec 20, 2022Biophysics

Engineering Rotating Apical-Out Airway Organoid for Assessing Respiratory Cilia Motility

P. Wijesekara, P. Yadav, L. A. Perkins, D. Stolz, J. M. Franks, S. Watkins, E. R. Jacome, S. L. Brody, A. Horani, J. Xu, A. Barati farimani, X. Ren

This study develops a rotating apical-out airway organoid model and computational framework to assess cilia motility and its defects in disease states.

bioRxiv · Jan 15, 2022Bioengineering

Computational Recipe for Designing Antibodies against the Ebola Virus

A. Barati Farimani, N. Aluru, E. Tajkhorshid, E. Jakobsson

This paper develops a computational method to predict viral escape mutations and design synthetic antibodies against Ebola virus by integrating bioinformatics, structural biology, and molecular dynamics simulations.

bioRxiv · Apr 4, 2020 · PreprintImmunology

Potential Neutralizing Antibodies Discovered for Novel Corona Virus Using Machine Learning

R. Magar, P. Yadav, A. Barati Farimani

This study uses machine learning to predict potential inhibitory antibodies against COVID-19 and identifies 8 stable candidates through bioinformatics and molecular dynamics simulations.

bioRxiv · Mar 14, 2020Immunology