Payton Bock

• Investigating the biology of aging and exceptional longevity, with a specific focus on understanding age-related changes in cancer biology.
• Utilizing multi-omics integration (DNA methylation, transcriptomics, proteomics) across pan-cancer datasets (e.g., TCGA) to identify molecular signatures associated with chronological age and clinical outcomes.
• Applying machine learning approaches (elastic net, random-forests) to build predictive models of biological age and explore relationships between predicted age, actual chronological age, and cancer aggressiveness.
• Performing bioinformatics analyses including differential expression analysis, Gene Set Enrichment Analysis (GSEA), and Cox proportional hazards modeling to link molecular markers of aging with patient survival and disease progression.

Completed research rotations (~8 weeks each)

• Lab of Dr. Francisco Naya: Performed qPCR validation and single-cell RNA sequencing (scRNA-seq) analysis to characterize the developmental effects of knocking down the long non-coding RNA Meg3 in mouse embryos.
• Lab of Dr. Xiaoling Zhang: Developed an improved genomic reference for scRNA-seq read alignment by filtering ambiguous reads mapped to low-mappability genomic regions, significantly reducing false positives in trans-QTL analyses related to Alzheimer's disease.
• Lab of Dr. Stefano Monti: Analyzed miRNA expression dysregulated by Benzo[a]pyrene exposure using differential expression analysis methods to identify potential biomarkers and mechanistic insights into lung cancer progression.

• Participated in Boston University's Bioinformatics Research and Interdisciplinary Training Experience. Researched under Dr. Xiaoling Zhang analyzing single-nuclei RNA sequencing data from the brain hippocampus region in mixed dementia patients.

• Academic-year internship focused on improving the treatment of brain cancer by investigating variation in blood-brain barrier function. Identified blood-brain barrier genes with the highest frequency of functionally impactful single-nucleotide polymorphisms in large cancer cohorts

• Worked under Dr. Sara Byron utilizing pharmacogenomics software to identify drug metabolism alterations in relapsed recurrent pediatric cancer patients. Selected as a speaker to represent TGen's Integrated Cancer Genomics division.