Traveling Back to the Future: Using Network Science to Unravel Evolutionary Conserved RNA Binding Proteins and Complexes Associated with Disease

SPRING 2018 RESEARCH INCUBATION AWARDEES

Pl: Simon Kasif, Biomedical Engineering, ENG
Co-Pls: Mark Crovella, Computer Science, CAS; Andrew Emili, Biochemistry, MED

This project aims to advance fundamental knowledge of biology and open new opportunities for developing early diagnostics, prognostics and perhaps even novel therapeutically promising approaches to a devastating disease, Alzheimer’s.The significant cost, time, and effort required for biological validations indicate that the predicted accuracies of human and mouse annotations must be raised to a much higher level using more targeted approaches and frameworks for efficient specialization of function prediction. Focusing efforts on a single (non-trivial) class of complexes, this project aims to significantly improve the accuracy of predictions, while at the same time developing methods that may subsequently be applied to other complexes and biological pathways. This project will develop, compare and validate novel computational network techniques to integrate all the relevant public data as well as novel experimental and genetic data to specifically identify new RNA binding proteins participating in RNA binding complexes that interact with genes associated with Alzheimer’s.

This work is funded by a Research Incubation Award made in January, 2018.