Brender, Jeffrey R.

Predicting the Effect of Mutations on Protein-Protein Binding Interactions through Structure-Based Interface Profiles

Brender, J. R., & Zhang, Y. (2015) · PLOS Computational Biology

Protein Structure and DynamicsComputational Drug Discovery Methods

Cited by 140

Imaging of glucose metabolism by 13C-MRI distinguishes pancreatic cancer subtypes in mice

Kishimoto, S., Brender, J. R., Crooks, D. R., Matsumoto, S., Seki, T., Oshima, N., Merkle, H., Lin, P., Reed, G., Chen, A. P., et al. (2019) · eLife

Advanced NMR Techniques and ApplicationsCancer, Hypoxia, and Metabolism

Cited by 41

Molecular imaging of the tumor microenvironment reveals the relationship between tumor oxygenation, glucose uptake, and glycolysis in pancreatic ductal adenocarcinoma

Yamamoto, K., Brender, J. R., Seki, T., Kishimoto, S., Oshima, N., Choudhuri, R., Adler, S. S., Jagoda, E. M., Saito, K., Devasahayam, N., et al. (2020) · Cancer Research

Cancer, Hypoxia, and MetabolismMedical Imaging Techniques and Applications

Cited by 37

Recent advances in automated protein design and its future challenges

Setiawan, D., Brender, J., & Zhang, Y. (2018) · Expert Opinion on Drug Discovery

Protein Structure and DynamicsChemical Synthesis and Analysis

Cited by 26

Rapid prediction of thermodynamically destabilizing tyrosine phosphorylations in cancers

Woodard, J., Liu, Z., Chegini, A. M., Tian, J., Bhowmick, R., Pennathur, S., Mashaghi, A., Brender, J., & Chandrasekaran, S. (2024) · Cell Reports Methods

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 4

A structural machine learning approach for rapid prediction of thermodynamically destabilizing tyrosine phosphorylations

Woodard, J., Liu, Z., Chegini, A. M., Tian, J., Bhowmick, R., Pennathur, S., Mashaghi, A., Brender, J. R., & Chandrasekaran, S. (2025) · Cell Reports Methods

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 3