Tokheim, Collin
Harvard University · Dana-Farber Cancer Institute
8 papers on CoChatORCID 0000-0003-1395-5378
Most cited papers
- Verified
Comprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell
Cancer Genomics and DiagnosticsGenomics and Rare Diseases
Cited by 2,256
- Verified
Comprehensive Characterization of Cancer Driver Genes and Mutations
Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018) · Cell
Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer
Cited by 552
- Verified
The Genomic Landscape of Response to EGFR Blockade in Colorectal Cancer
Bertotti, A., Papp, E., Jones, S., Adleff, V., Anagnostou, V., Lupo, B., Sausen, M., Phallen, J., Hruban, C. A., Tokheim, C., et al. (2015) · Nature
Colorectal Cancer Treatments and StudiesLung Cancer Treatments and Mutations
Cited by 479
- Verified
Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics
Ding, L., Bailey, M. H., Porta-Pardo, E., Thorsson, V., Colaprico, A., Bertrand, D., Gibbs, D. L., Weerasinghe, A., Huang, K.-L., Tokheim, C., et al. (2018) · Cell
Cancer Genomics and DiagnosticsChromatin Remodeling and Cancer
Cited by 399
- Verified
Therapeutically Increasing MHC-I Expression Potentiates Immune Checkpoint Blockade
Gu, S. S., Zhang, W., Wang, X., Jiang, P., Traugh, N., Li, Z., Meyer, C., Stewig, B., Xie, Y., Bu, X., et al. (2021) · Cancer Discovery
Cancer Immunotherapy and BiomarkersImmunotherapy and Immune Responses
Cited by 273
- Verified
Determinants of transcription factor regulatory range
Chen, C.-H., Zheng, R., Tokheim, C., Dong, X., Fan, J., Wan, C., Tang, Q., Brown, M., Liu, J. S., Meyer, C. A., et al. (2020) · Nature Communications
Genomics and Chromatin DynamicsGene Regulatory Network Analysis
Cited by 85
- Verified
Machine Learning Modeling of Protein-Intrinsic Features Predicts Tractability of Targeted Protein Degradation
Zhang, W., Roy Burman, S. S., Chen, J., Donovan, K. A., Cao, Y., Shu, C., Zhang, B., Zeng, Z., Gu, S., Zhang, Y., et al. (2022) · Genomics, Proteomics & Bioinformatics
Protein Degradation and InhibitorsComputational Drug Discovery Methods
Cited by 51
- Verified
Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation
Zhang, W., Roy Burman, S. S., Chen, J., Donovan, K. A., Cao, Y., Zhang, B., Zeng, Z., Zhang, Y., Li, D., Fischer, E. S., et al. (2021) · Genomics Proteomics & Bioinformatics
Protein Degradation and InhibitorsComputational Drug Discovery Methods
Cited by 51
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