Details of Research Project: cell-cell communication (CCC) mediated by specific ligand-receptor interaction modulates several functions necessary for maintaining human health. Dysregulation in these interactions are observed in several disease conditions including heart failure chronic kidney disease cross-organ fibrosis. Current methods to quantify CCC are limited in terms of a) predicting the impact of these interactions of downstream functions in a cell and b) accounting for the impact on the overall phenotype. The goal of this project is to conduct a comprehensive benchmark of factors such changes in levels of ligands receptors and their downstream pathways in order to identify key ligand-receptor interactions associated with cross-organ fibrosis.
Goals/Outcomes of the Research Project: The goal of the project is to:
Develop a framework to compare CCC across organs
Evaluate the impact of ligand-receptor interactions in predicting their downstream pathway activation
Creation of a web-portal to host pre-computed cross-organ CCC interactions
Preparation of a final report and presentation
The ideal candidate is fluent in Python and R programming languages. Experience in data pre-processing feature extraction methods supervised and unsupervised machine learning model evaluation and validation is essential. Previous knowledge of single-cell transcriptomics is desirable. Performs other related duties assigned.
Required Experience:
Intern
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