Dr Giuseppe Nicosia
Solving biological problems with algorithms
On first glance at Dr Giuseppe Nicosia’s research you may not realise that he’s a computer scientist, as his results focus on solving real-world biological problems. However, it was the forefathers of computer science who first inspired his work.
When Giuseppe was a student he read the seminal papers of Alan Turing and John von Neumann. Their last works were on biological problems, which inspired him.
"At the end of their lives, they were using algorithms, using computer systems to address relevant biological problems. They saw that it is possible to understand and program our cells, our tissues, our organs."
contributing to metabolism research
In collaboration with the University of Cambridge Systems Biology Centre, Giuseppe’s current research focus is to use the computational analysis of the biochemical pathways needed to carry out basic metabolic functions in the cell, to then discover the minimal and most important genes for metabolism.
Giuseppe explains how this will be relevant for understanding disease, pathologies, and disorders. "This is because we’ll have a sort of redundancy – we will discover the set of redundancy genes, non-essential genes, and therefore understand more about the most important genes for the metabolism. We can then try to match them with the disease.”
tackling big problems
Giuseppe believes that humanity needs a pan-disciplinary research approach to tackle big problems, which is why he uses approaches and principles from computer science, maths and engineering for his work in synthetic biology.
“Synthetic biology is a newer field – it’s really only been around in the last few decades. It’s possible to program biology; it’s possible to program our cells; it’s possible to design our cells. This has many applications, for instance producing useful chemicals like bioplastics and biofuel, and also to discover important genes.”
In the past few years, he has already tackled several problems through research, including maximising the efficiency of the solar cell and creating the design of the metabolic network for the production of ethanol.
"The ultimate goal for a lot of my research involves designing, analysing, optimising, learning from big data in order to understand the human metabolism. Our cells are performing immensely intricate, impossibly complex algorithms continuously, we just can’t see it yet."
Real-world application of Artificial intelligence
Giuseppe teaches a new module on artificial intelligence which is open to both undergraduate and postgraduate students. By covering traditional concepts and linking those to real-world applications such as synthetic biology and design automation, Giuseppe’s research will feature heavily in illustrating current examples.
“In the first part of the module we will cover ‘traditional’ artificial intelligence concepts, but in the last part we will link to real-world applications and I will absolutely be using my research to illustrate this. We will also look beyond my research at other state-of-the-art artificial intelligence applications, like the algorithms needed for self-driving cars, multi-task learning, self-learning algorithms, and life-long learning algorithms.”