Author

O. Al-Dalahmah

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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Cancer Biology· 2 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Organism:human· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:differential expression· 2 Assay:imaging· 2 Approach:statistical model· 2 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

P. Canoll· 3 shared A. Hawkins-Daarud· 2 shared A. Save· 2 shared D. Boyett· 2 shared J. Grinband· 2 shared J. Li· 2 shared K. R. Swanson· 2 shared A. Dovas· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersCancer Biology

P. Canoll

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3 papers

Recent·Most cited

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

H. Wang, M. G. Argenziano, H. Yoon, D. Boyett, A. Save, P. Petridis, W. Savage, P. Jackson, A. Hawkins-Daarud, N. Tran, L. Hu, O. Al-Dalahmah, J. N. Bruce, J. Grinband, K. R. Swanson, , J. Li

This paper develops BioNet, a biologically-informed deep learning model, to predict intratumoral heterogeneity in post-treatment glioblastoma using MRI and biopsy data, showing improved performance over existing methods.

npj Digital Medicine · Oct 19, 2024Peer-reviewedCancer Biology

Mapping multiregional imaging-localized biopsies to MRI habitats reveals biologically significant glioma tissue states and associated patterns of cohabitating cellular subpopulations

L. Curtin, K. M. Bond, P. R. Jackson, A. Hawkins-Daarud, S. Velez, N. Shakir, J. C. Urcuyo, G. De Leon, K. W. Singleton, J. M. Langworthy, K. Clark-Swanson, Y. Lassiter-Morris, L. Paulson, C. Sereduk, C. Krishna, , K. R. Swanson

The paper maps MRI-localized glioma biopsies to MRI habitats, identifying transcriptional tissue states and their association with cellular subpopulations and MRI features.

bioRxiv · Mar 23, 2022 · PreprintCancer Biology

Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states

O. Al-Dalahmah, M. Argenziano, A. Kannan, A. Mahajan, J. Furnari, F. Paryani, D. Boyett, A. Save, N. Humala, F. Khan, J. Li, H. Lu, Y. Sun, J. Tuddenham, a. r. goldberg, , P. Canoll

The paper identifies three tissue states in glioblastoma microenvironments using snRNAseq and spatial transcriptomics, linking them to metabolic pathways and clinical outcomes.

bioRxiv · Jul 6, 2021Pathology