Author

Parisa Mazrooei

Genentech

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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Bioinformatics· 1 Immunology· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:differential expression· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Assay:ChIP-seq· 1 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Saroja RamanujaniD· 2 shared Allen NguyeniD· 1 shared Amelia Au‐Yeung· 1 shared Benjamin Haibe‐KainsiD· 1 shared Bingyuan Chen· 1 shared Chikara Takahashi· 1 shared Courtney SchiffmaniD· 1 shared Daniel O’Neil· 1 shared

Activity by Year

2018-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersImmunology

Saroja RamanujanORCID

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3 papers

Recent·Most cited

Molecular characterization of response to etrolizumab and anti-TNF reveals treatment resistance in ulcerative colitis is associated with the abundance of residual neutrophil subsets and inflammatory fibroblast populations

Shadi Toghi Eshghi, John Mark B. Gubatan, Parisa Mazrooei, Luis Quintanilla, Allen Nguyen, Amelia Au‐Yeung, Derek Holman, Chikara Takahashi, Courtney Schiffman, William E. O’Gorman, Mary E Keir, Saroja Ramanujan, Stephan Rogalla, Jason A. Hackney, Jacqueline McBride

The paper identifies treatment resistance in ulcerative colitis linked to residual neutrophil subsets and inflammatory fibroblasts using single-cell analysis of biopsy data.

bioRxiv · Jul 2, 2024 · PreprintImmunology

Leveraging protein language and structural modelsfor early prediction of antibodies with fast clearance

Parisa Mazrooei, Daniel O’Neil, Saeed Izadi, Bingyuan Chen, Saroja Ramanujan

This paper predicts antibody clearance using deep learning and physicochemical features, showing comparable performance to physicochemical models.

bioRxiv · Jun 8, 2024 · PreprintPharmacology & Toxicology

CREAM: Clustering of genomic REgions Analysis Method

Seyed Ali Madani Tonekaboni, Parisa Mazrooei, Victor Kofia, Benjamin Haibe‐Kains, Mathieu Lupien

CREAM identifies COREs from cis-regulatory data, outperforming ROSE, and shows their enrichment near essential genes and TAD boundaries.

bioRxiv · Mar 20, 2018 · PreprintBioinformatics