Master’s Thesis Presentation • Bioinformatics • Prediction of AL Amyloidosis Using Deep Learning

Please note: This master’s thesis presentation will take place online.

Anupa Murali, Master’s candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Bin Ma

AL amyloidosis (amyloid light chain or primary amyloidosis) is a rare type of amyloidosis, which occurs when abnormal immunoglobulin light chain (LC) proteins in the body misfold and accumulate on the heart, the kidneys, and the other organs. It can be potentially fatal or can cause permanent damage to the organs in the body, especially in cases where the diagnosis does not arrive early enough or where the treatment does not begin on time.

In order to facilitate timely diagnosis of the disease before the symptoms start fully exhibiting themselves and before the damage to the organs becomes significant, we present a computational solution in this thesis, called “DALAD”, which is based on (convolutional) deep learning networks and takes in an LC sequence from a patient as the input, and determines with high confidence whether the patient has the disease or not.

We develop and test multiple versions of DALAD, which are characterized by the type of sequences they have been trained on and by the types of features they incorporate to make the predictions. We establish the following for DALAD.

To join this master’s thesis presentation on Zoom, please go to https://uwaterloo.zoom.us/j/92859196002.