Grace Rose

Highly motivated undergraduate researcher with hands on experience in laboratory-based research and data analysis. Demonstrates a strong ability to quickly digest new information and thrive in a dynamic, fast paced environment. Proactive in seeking out learning opportunities and taking initiative to drive projects forward. Committed to continuous professional growth and contributing effectively to collaborative research endeavors.

Biochemistry: 

Throughout the semester, I engaged in a comprehensive case study that involved analyzing laboratory data and patient symptoms to gain an in-depth understanding of biochemical pathways.

Protein and Enzyme Characterization: Utilized UniProt to retrieve detailed information on proteins and enzymes and accessed structural data from the RCSB Protein Data Bank to understand molecular conformations.

Data Interpretation: Interpreted experimental data from scientific literature to aid in comprehension of metabolic processes, applying appropriate statistical tests to biochemical datasets to assist in deciphering results in a metabolic context.

Molecular Docking Simulations: Employed SwissDock to conduct and interpret molecular docking simulations, integrating biochemical and clinical data to explain symptom aggravation and understand drug-induced inhibition of metabolic pathways.

Molecular Genetics Lab: 

During this course, I participated in an extensive research project employing both forward and reverse genetic screens to understand the genetic basis for fungal resistance to the anti-mycotic drug Manogepix.

Experiments:

Orchestrated an experiment to determine the dosage sensitivity of S. cerevisiae with respect to survival and growth in Manogepix. Then conducted screens to obtain sub strains that showed resistance to Manogepix. Genomic DNA was then acquired from these sub strains and sent along with DNA from the parental strain for whole genome sequencing to identify genetic variants. Finally, an experiment to engineer mutations in the endogenous Gwt1 gene of S. cerevisiae was carried out based on previous structural work in order to understand how mutations in this gene affect Manogepix sensitivity.

Analysis Techniques:

Utilized software’s such as Geneious and Breseq to analyze DNA sequences and identify mutations and determine the plausible phenotypic effects