Natalie D
- Research Program Mentor
PhD candidate at University of California
Expertise
Medicine, Bioinformatics, Computational Biology, Genetics, Genomics, Data Science
Bio
I received my PhD in Biomedical Sciences with a specialization in Bioinformatics from the University of California, San Diego in 2023, and earned a BSc in Pharmaceutical Chemistry with a minor in Quantitative Biology & Bioinformatics, summa cum laude, from UC Davis. My research background centers on complex and highly prevalent metabolic disorders, such as type 2 diabetes, cardiovascular disease, cancer, and neurodegeneration, with a focus on leveraging cutting-edge genomic technologies and machine learning to improve our understanding, diagnosis, and treatment of these conditions. By applying human genetics, I am interested identifying disease-related genes that may serve as potential drug targets or offer insights into underlying disease mechanisms. My work combines data science approaches including data cleaning, computation, and visualization with biological and clinical knowledge to extract meaningful insights from large, diverse human datasets. I additionally have extensive experience of involvement in the broader scientific community by publishing my findings in peer-reviewed journals and developing public-facing research websites that make complex data and findings more accessible. Outside of research, I enjoy spending time outdoors, especially playing tennis, rock climbing, and hiking.Project ideas
Identification and Prioritization of Novel Type 2 Diabetes Genes
With the advent of the internet and data sharing platforms, several public human genetic databases have been established (i.e. GWAS Catalog, Common Metabolic Disease Knowledge Portal) in which scientific researchers have deposited their research findings for others to examine. Much of this data remains under-utilized but researchers still continue to add more data to these databases. In this potential project, one could aggregate the genetic findings from type 2 diabetes studies from existing public databases to identify and prioritize novel genes of interest which may be play crucial roles in type 2 diabetes development. Such a project could also extend to different diseases, depending on the student's research interests!
