Harvard Catalyst Profiles

The study will illustrate the role of cell-cell interactions in understanding complex biological processes and their dysregulation in diseases. These interactions govern crucial mechanisms in multicellular organisms, orchestrating developmental pathways, immune responses, and tissue repair through intricate signaling mechanisms. We can gain critical insights into cellular communication by analyzing spatial gene expression patterns, offering a deeper understanding of disease markers and complex communication networks within biological systems. Using single-cell RNA-seq, we can identify cellular connections, unveiling the roles of specific cells as receptors for signaling molecules secreted by neighboring cells. The student will design the project in terms of which datasets to use and what specific questions can be asked when comparing cell-cell interactions with normal and diseased tissue. Furthermore, the student will apply a selected set of cell-cell interaction algorithms to identify these interactions and perform a comparative analysis of different algorithms. The student will then compile interaction profiles from different algorithms to identify common features. A differential analysis of interactions between normal and diseased tissues will be performed to understand how interactions change between these conditions. The student will learn how to effectively represent observations using appropriate graphs and plots. They will also discuss their observations in lab meetings and other departmental meetings.