Author

N. Nerlakanti

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 Approach:statistical model· 2 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

A. Basu· 1 shared A. K. Miller· 1 shared A. S. Silva· 1 shared B. Manley· 1 shared C. Lynch· 1 shared C. O'Farrelly· 1 shared D. Basanta· 1 shared D. Lemanne· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperCancer Biology

A. Basu

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2 papers

Recent·Most cited

The bone ecosystem facilitates multiple myeloma relapse and the evolution of heterogeneous proteasome inhibitor resistant disease

R. T. Bishop, A. K. Miller, M. Froid, N. Nerlakanti, T. Li, J. Frieling, M. Nasr, K. Nyman, P. Sudalagunta, R. Canevarolo, A. S. Silva, K. T. Shain, C. Lynch, D. Basanta

This study uses a hybrid agent-based model to show the bone ecosystem promotes multiple myeloma relapse and the evolution of proteasome inhibitor-resistant disease by providing a protective niche for drug-sensitive cells.

bioRxiv · Nov 13, 2022 · PreprintCancer Biology

Harnessing patient-specific response dynamics to optimize evolutionary therapies for metastatic clear cell renal cell carcinoma - Learning to adapt

I. C. Sorribes, A. Basu, R. Brady, P. M. Enriquez-Navas, X. Feng, J. N. Kather, N. Nerlakanti, R. Stephens, M. Strobl, I. Tavassoly, N. Vitos, D. Lemanne, B. Manley, C. O'Farrelly, H. Enderling

This paper develops a dynamic tumor-immune model to predict patient response to treatment using NLR as a biomarker and simulates optimal therapies for virtual RCC patients.

bioRxiv · Feb 28, 2019 · PreprintCancer Biology