Author

P. Habib

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 Cancer Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Organism:mouse· 2 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:proteomics· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

A. Beck· 1 shared A. Chawla· 1 shared A. Hamwieh· 1 shared A. M. Alsamman· 1 shared A. Rothrauff· 1 shared A. V. Joglekar· 1 shared B. Bui· 1 shared C. K. Petritsch· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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1 shared paperCancer Biology

A. Beck

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Temporal dynamics and genomic programming of plasma cell fates

G. K. M. Vijay, M. Zhou, K. Thakkar, A. Rothrauff, A. Chawla, D. Chen, L. Lau, P. Habib, K. Chetal, P. Chhibbar, J. Fan, J. Das, A. V. Joglekar, L. Borghesi, N. Salomonis, , H. Singh

This study identifies a novel PC transition state and shows that long-lived plasma cells arise from late-phase GC responses through TIGIT-dependent clonal expansion.

bioRxiv · Aug 27, 2023 · PreprintImmunology

BRAF/MEK Inhibition Induces Cell State Transitions Boosting Immune CheckpointSensitivity in BRAFV600E-mutant Glioma

Y. L. Xing, D. Panovska, J.-W. Park, S. Grossauer, K. Koeck, B. Bui, E. Nasajpour, J. J. Nirschl, Z.-P. Feng, P. Cheung, P. Habib, R. Wei, J. Wang, W. Thomason, J. Xiu, , C. K. Petritsch

This study shows that BRAF/MEK inhibition induces cell state transitions in BRAFV600E-mutant gliomas, leading to PD-L1 upregulation and immune evasion, which can be overcome by combining with immune checkpoint inhibition.

bioRxiv · Feb 3, 2023Cancer Biology

COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification

P. Habib, A. M. Alsamman, M. Saber-Ayad, S. E. Hassanein, A. Hamwieh

The paper introduces a deep learning tool called COVIDier that classifies coronaviruses genomes with high accuracy, outperforming traditional methods like BLAST.

bioRxiv · May 3, 2020 · PreprintBioinformatics