Author

A. Vo

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

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Research Focus:synaptic & neural circuits· 1

Frequent Co-Authors

C. Gekas· 1 shared C. Jeffries· 1 shared C. Lu· 1 shared C. Mao· 1 shared C. Ramathal· 1 shared D. Verduzco· 1 shared E. Murphy· 1 shared J. O. Nugent· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

C. Gekas

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Author profile →

2 papers

Recent·Most cited

TCGADEPMAP -- Mapping Translational Dependencies and Synthetic Lethalities within The Cancer Genome Atlas

X. Shi, C. Gekas, D. Verduzco, S. Petiwala, C. Jeffries, C. Lu, E. Murphy, T. Anton, A. Vo, Z. Xiao, P. Narayanan, M. Barnes, S. Roy, C. Ramathal, M. J. Flister, Z. Dezso

TCGADEPMAP maps translational tumor dependencies and synthetic lethality using TCGA data, identifying novel targets like PAPSS1/2 with clinical implications.

bioRxiv · Mar 24, 2022 · PreprintCancer Biology

Deep learning for cancer type classification

Z. Zeng, C. Mao, A. Vo, J. O. Nugent, S. A. Khan, S. E. Clare, Y. Luo

This study introduces DeepCues, a deep learning model that improves cancer type classification using DNA sequencing data, achieving 77.6% accuracy on TCGA data and showing significant improvement over conventional methods.

bioRxiv · Apr 17, 2019 · PreprintCancer Biology