miRNAS Sequence Embedding For Pathway Detection And Selectivity

Lead Research Organisation: Queen Mary University of London
Department Name: School of Engineering & Materials Scienc

Abstract

TO BE UPDATED NOV 2023 (AT YEAR 2 PROGRESSION)

The search to get a medication that can curb or possibly cure diseases and afflictions is still at the forefront of medical research. What if the cure was already in our DNA? One such potential solution of study is microRNAs. One of the complexities associated with the living cell structure is the multiple, many to many interactions between microRNAs and messenger RNAs. This research hopes to understand the relationship between microRNAs, messenger RNAs and the Pathways that bring them together using multi-tasking machine learning techniques to create medications that carry the right combinations of microRNAs to solve specific ailments. This includes researching microRNAs clusters, Pathway clusters and possibly correlations amongst them to get a wholistic picture of interaction. Data used will be taken from both humans and animals. Multi-Task architectures include Path-Sluice with Task Affinity, Feature sharing and Shared Trunk Hierarchal.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/V519935/1 30/09/2020 29/04/2028
2601245 Studentship EP/V519935/1 30/09/2021 29/09/2025 Zimpi Komo