Brannan, Kristopher W.

Control of RNA Pol II Speed by PNUTS-PP1 and Spt5 Dephosphorylation Facilitates Termination by a “Sitting Duck Torpedo” Mechanism

Cortazar, M. A., Sheridan, R. M., Erickson, B., Fong, N., Glover-Cutter, K., Brannan, K., & Bentley, D. L. (2019) · Molecular Cell

Genomics and Chromatin DynamicsRNA Research and Splicing

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Effects of Transcription Elongation Rate and Xrn2 Exonuclease Activity on RNA Polymerase II Termination Suggest Widespread Kinetic Competition

Fong, N., Brannan, K., Erickson, B., Kim, H., Cortazar, M. A., Sheridan, R. M., Nguyen, T., Karp, S., & Bentley, D. L. (2015) · Molecular Cell

Genomics and Chromatin DynamicsRNA Research and Splicing

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A visual–omics foundation model to bridge histopathology with spatial transcriptomics

Chen, W., Zhang, P., Tran, T. N., Xiao, Y., Li, S., Shah, V. V., Cheng, H., Brannan, K. W., Youker, K., Lai, L., et al. (2025) · Nature Methods

Single-cell and spatial transcriptomicsAI in cancer detection

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HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

Jin, W., Brannan, K. W., Kapeli, K., Park, S. S., Tan, H. Q., Gosztyla, M. L., Mujumdar, M., Ahdout, J., Henroid, B., Rothamel, K., et al. (2023) · Molecular Cell

RNA Research and SplicingMachine Learning in Bioinformatics

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HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

Jin, W., Brannan, K. W., Kapeli, K., Park, S. S., Tan, H. Q., Gosztyla, M. L., Mujumdar, M., Ahdout, J., Henroid, B., Rothamel, K., et al. (2022) · Molecular Cell

RNA Research and SplicingMachine Learning in Bioinformatics

Cited by 52