Author

V. Anagnostou

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Cancer Biology· 2 Immunology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:deep learning· 4 Organism:human· 4 Research Focus:gene regulatory network inference· 3 Research Focus:cell type annotation· 2 Assay:CITE-seq· 2 Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Approach:statistical model· 2

Frequent Co-Authors

R. Karchin· 3 shared A. Balan· 2 shared X. M. Shao· 2 shared A. B. Riemer· 1 shared A. Boire· 1 shared A. G. Dykema· 1 shared A. J. Munoz· 1 shared A. Omdahl· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersCancer Biology

R. Karchin

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

A generative reference grammar of healthy TCR repertoires reveals cancer-associated immune remodeling

A. Balan, Y. Elhanati, K. E. Meza Landeros, M. De Almeida Mendes, J. Lai, S. S. A. Zaidi, M. Unal, B. Y. S. Kim, C.-H. G. Lucas, E. Runco, V. K. Puduvalli, J. Gantchev, C. A. Whittaker, P. Sharma, V. Tabar, , R. Karchin

CRAFT, a transformer model, learns a generative grammar of healthy TCR repertoires to detect cancer-associated immune remodeling through structured deviations in sequence space.

bioRxiv · Jun 20, 2026 · PreprintCancer Biology

SpliceMutr enables pan-cancer analysis of splicing-derived neoantigen burden in tumors

T. Palmer, M. D. Kessler, X. M. Shao, A. Balan, M. Yarchoan, N. Zaidi, T. Y. Lopez-Vidal, A. Saeed, J. Gore, N. Azad, E. Jaffee, A. V. Favorov, V. Anagnostou, R. Karchin, D. Gaykalova, , E. J. Fertig

SpliceMutr quantifies splicing-derived neoantigens across cancers, finding correlations with immune biomarkers and treatment response.

bioRxiv · May 26, 2023Cancer Biology

Lung tumor-infiltrating Treg have divergent transcriptional profiles and function linked to checkpoint blockade response

A. G. Dykema, J. Zhang, B. Zhang, L. S. Cheung, Z. Zeng, C. M. Cherry, T. Li, J. X. Caushi, M. Nishimoto, S. Connor, Z. Ji, A. J. Munoz, W. Hou, W. Zhan, D. Singh, , K. N. Smith

The paper identifies 10 subsets of lung cancer-infiltrating Tregs, showing one subset is suppressive and linked to anti-PD-1 resistance while another is Th1-like and associated with PD-1 response.

bioRxiv · Dec 13, 2022 · PreprintImmunology

High-throughput prediction of MHC Class I and Class II neoantigens with MHCnuggets

X. M. Shao, R. Bhattacharya, J. Huang, I. K. A. Sivakumar, C. Tokheim, L. Zheng, D. HIrsch, B. Kaminow, A. Omdahl, M. Bonsack, A. B. Riemer, V. Velculescu, V. Anagnostou, K. Pagel, R. Karchin

The paper introduces MHCnuggets, a deep learning method for predicting MHC class I and II neoantigen binding, showing improved performance and scalability across 26 cancer types.

bioRxiv · Oct 4, 2019Immunology