Author

Zarifeh Heidari Rarani

University of PittsburghORCID 0009-0000-4094-4469Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Immunology· 1 Scientific Communication & Education· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Approach:deep learning· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Assay:ATAC-seq· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Jishnu DasiD· 3 shared Swapnil KeshariiD· 3 shared Akanksha SachaniD· 2 shared Harinder SinghiD· 2 shared Nicholas A. PeaseiD· 2 shared Abhinav K Jain· 1 shared Aditi U. GurkariD· 1 shared Akash KishoreiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersSystems Biology

Jishnu DasORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Systems BiologybioRxivPreprintSep 29, 2026

Interpretable machine learning coupled to gene regulatory networks uncovers subcircuits underlying cell fate decisions

Zarifeh Heidari Rarani, Swapnil Keshari, Akanksha Sachan…·Jishnu Das

FOCAL couples interpretable machine learning with gene regulatory networks to identify regulatory subnetworks underlying cell fate decisions in B and T cells.

DOI 10.64898/2026.09.28.754797

humanbulk RNA-seq

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ImmunologybioRxivPreprintApr 23, 2025

Multi-scale gene regulatory networks for resolving transcription factor and autoimmune variant impacts on human B cell fate dynamics

Nicholas A. Pease, Jing‐Yu Fan, Swapnil Keshari…·Harinder Singh

3 citations

humanscRNA-seq

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Scientific Communication & EducationbioRxivPreprintMar 5, 2025

Cracking the code of co-authorship networks geo-temporally using interpretable machine learning

Swapnil Keshari, Zarifeh Heidari Rarani, Akash Kishore, Jishnu Das

The paper analyzes co-authorship networks using interpretable machine learning to identify research trends and patterns in scientific collaboration over time.

1 citation

deep learningstatistical model

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