Shelli Kesler

Brain Health Neuroscience Lab

Center for Computational Oncology - Oden Institute for Computational Engineering and Sciences

Biography

Dr. Kesler is a cognitive neuroscientist with expertise in neuroimaging, neuropsychology, biostatistics, machine learning and computer programming.  The focus of her research concerns the effects of cancer and its treatments on brain network (connectome) organization. She aims to improve precision health management of cognitive toxicities in patients with non-CNS cancer though connectome-based subtyping and prognosis of cognitive dysfunction.  She also examines the relationships between the connectome, cognition, and survival in patients with CNS cancer.  She has obtained over $14 million in external grant funding including four National Institutes of Health R01's and the prestigious National Institutes of Health Director's New Innovator Award. 

Publications and Projects

• NCBI Bibliography
• ResearchGate

Current Funding

• R01CA226080 (PI) "Predicting Long-Term Chemotherapy-Related Cognitive Impairment"
• R01CA172145(PI) "Very Long-Term Neurocognitive Outcomes in Breast Cancer Survivors"
• R03CA241862 (PI) "Using Connectomics and Machine Learning to Predict Survival in Diffuse Glioma"
• R56AG071152 (Co-I) "Delaying Alzheimer's Disease Progression Through Intranasally Administered Nano-Antioxidants"
• UT Frontiers of Neuroscience (MPI) "Rhesus Macaque Model of Chemotherapy-Related Cognitive Impairments and Neurodegeneration"

Research Resources and Data

Software

Software toolboxes for conducting connectome and machine learning analyses https://github.com/srkesler/bnets

Predictive Models

• Predicting probability of Alzheimer’s disease from T1 weighted MRI (Kesler, SR, et al. 2017. Alzheimers Dement (Amst), 9, pp. 67-75.)

Data

Transgenic 5XFAD and non-transgenic functional and structural connectome data from Kesler, SR, et al. 2018. Netw Neurosci, 2, pp. 241-258.