Author

A. Dhakal

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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Biochemistry· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cancer & tumor microenvironment· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:graph neural network· 1 Organism:mouse· 1 Assay:protein structure· 1

Frequent Co-Authors

A. M. Holderbaum· 1 shared B. M. Murphy· 1 shared C. E. Burd· 1 shared C. J. Burd· 1 shared J. Cheng· 1 shared M. Chen· 1 shared M. Fort· 1 shared M. S. Bodnar· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

A. M. Holderbaum

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Author profile →

2 papers

Recent·Most cited

Predicting Protein-Ligand Binding Structure Using E(n) Equivariant Graph Neural Networks

A. Dhakal, R. Gyawali, J. Cheng

The paper introduces an E(n) Equivariant Graph Neural Network to predict ligand-protein binding structures, showing promising results for drug design.

bioRxiv · Aug 6, 2023 · PreprintBiochemistry

Functional differences drive the selection of NRAS mutants in melanoma

B. M. Murphy, T. J. Weiss, A. M. Holderbaum, A. Dhakal, M. Fort, M. S. Bodnar, M. Chen, C. J. Burd, V. COPPOLA, C. E. Burd

This study shows that specific NRAS mutants drive melanoma formation in mice, with Q61R and Q61K being the most effective, while others like G12D or Q61Q are not.

bioRxiv · Jan 15, 2021 · PreprintCancer Biology