Shah, Sohrab P.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups

METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature

Breast Cancer Treatment StudiesCancer Genomics and Diagnostics

Cited by 6,097

The clonal and mutational evolution spectrum of primary triple-negative breast cancers

Shah, S. P., Roth, A., Goya, R., Oloumi, A., Ha, G., Zhao, Y., Turashvili, G., Ding, J., Tse, K., Haffari, G., et al. (2012) · Nature

Cancer Genomics and DiagnosticsBreast Cancer Treatment Studies

Cited by 1,967

ARID1A Mutations in Endometriosis-Associated Ovarian Carcinomas

Wiegand, K. C., Shah, S. P., Al-Agha, O. M., Zhao, Y., Tse, K., Zeng, T., Senz, J., McConechy, M. K., Anglesio, M. S., Kalloger, S. E., et al. (2010) · New England Journal of Medicine

Chromatin Remodeling and CancerOvarian cancer diagnosis and treatment

Cited by 1,712

Eleven grand challenges in single-cell data science

Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,327

Tumor-Associated Macrophages and Survival in Classic Hodgkin's Lymphoma

Steidl, C., Lee, T., Shah, S. P., Farinha, P., Han, G., Nayar, T., Delaney, A., Jones, S. J., Iqbal, J., Weisenburger, D. D., et al. (2010) · New England Journal of Medicine

Lymphoma Diagnosis and TreatmentImmune cells in cancer

Cited by 1,262

Harnessing multimodal data integration to advance precision oncology

Boehm, K. M., Khosravi, P., Vanguri, R., Gao, J., & Shah, S. P. (2022) · Nature Reviews Cancer

Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and Education

Cited by 662

deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

McPherson, A., Hormozdiari, F., Zayed, A., Giuliany, R., Ha, G., Sun, M. G. F., Griffith, M., Heravi Moussavi, A., Senz, J., Melnyk, N., et al. (2011) · PLoS Computational Biology

Cancer Genomics and DiagnosticsGenomics and Phylogenetic Studies

Cited by 557

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer

Vanguri, R. S., Luo, J., Aukerman, A. T., Egger, J. V., Fong, C. J., Horvat, N., Pagano, A., Araujo-Filho, J. D. A. B., Geneslaw, L., Rizvi, H., et al. (2022) · Nature Cancer

Cancer Immunotherapy and BiomarkersRadiomics and Machine Learning in Medical Imaging

Cited by 395

Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer

Boehm, K. M., Aherne, E. A., Ellenson, L., Nikolovski, I., Alghamdi, M., Vázquez-García, I., Zamarin, D., Long Roche, K., Liu, Y., Patel, D., et al. (2022) · Nature Cancer

Ovarian cancer diagnosis and treatmentRadiomics and Machine Learning in Medical Imaging

Cited by 357

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models

Ding, J., Condon, A., & Shah, S. P. (2018) · Nature Communications

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 337

Molecular and genetic characterization of MHC deficiency identifies EZH2 as therapeutic target for enhancing immune recognition

Ennishi, D., Takata, K., Béguelin, W., Duns, G., Mottok, A., Farinha, P., Bashashati, A., Saberi, S., Boyle, M., Meissner, B., et al. (2019) · Cancer Discovery

Lymphoma Diagnosis and TreatmentCancer Immunotherapy and Biomarkers

Cited by 318

Genome variation in Cryptococcus gattii, an emerging pathogen of immunocompetent hosts

D’Souza, C. A., Kronstad, J. W., Taylor, G., Warren, R., Yuen, M., Hu, G., Jung, W. H., Sham, A., Kidd, S. E., Tangen, K., et al. (2011) · mBio

Fungal Infections and StudiesPlant Pathogens and Fungal Diseases

Cited by 202

Automated Real-World Data Integration Improves Cancer Outcome Prediction

Jee, J., Fong, C., Pichotta, K., Tran, T. N., Luthra, A., Waters, M., Fu, C., Altoe, M., Liu, S.-Y., Maron, S. B., et al. (2024) · Nature

Machine Learning in HealthcareCancer Genomics and Diagnostics

Cited by 188

Luminal breast epithelial cells of BRCA1 or BRCA2 mutation carriers and noncarriers harbor common breast cancer copy number alterations

Williams, M. J., Oliphant, M. U. J., Au, V., Liu, C., Baril, C., O’Flanagan, C., Lai, D., Beatty, S., Van Vliet, M., Yiu, J. C., et al. (2024) · Nature Genetics

Cancer Genomics and DiagnosticsBRCA gene mutations in cancer

Cited by 34

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression

Ligero, M., Serna, G., El Nahhas, O. S. M., Sansano, I., Mauchanski, S., Viaplana, C., Calderaro, J., Toledo, R. A., Dienstmann, R., Vanguri, R. S., et al. (2024) · Cancer Research Communications

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 22

Abstract 5721: Automated annotation for large-scale clinicogenomic models of lung cancer treatment response and overall survival

Jee, J., Fong, C., Pichotta, K., Tran, T., Luthra, A., Altoe, M., Maron, S., Shen, R., Liu, S.-Y., Waters, M., et al. (2023) · Cancer Research

Lung Cancer Treatments and MutationsRadiomics and Machine Learning in Medical Imaging

Cited by 4