About his PhD project

Mitochondria are essential organelles, which produce cellular energy in the form of ATP. They are also involved in many other cellular processes and functionally adapt to cellular needs. In this project, we will combine deep learning with mitochondrial computational biology to develop "mito-learner", a deep learning based algorithm for predicting mitochondrial functional states of tumors. The expression states of genes involved in mitochondrial functions (mito-genes) represented as vectors will be used to build image representations allowing the use of image-based deep learning architectures like CNNs and Transformers. In this project, we want to test different representations and models, and further develop visual interpretability methods to identify genes that can discriminate between healthy and tumor tissues, as well as different tumor stages.