Giorgia Del Missier

Ciao 👋🏽 I’m Giorgia!

I am a computational biologist, and I am passionate about solving sustainability challenges in bioengineering using AI. Currently, I am leading the computational team at the Ledesma-Amaro Synthetic Biology group at Imperial College London.

I have a strong background in bioinformatics, modelling and molecular biology and I am skilled in data analysis using Python and R.

I’m committed to promoting open, collaborative science and create sustainable solutions to our planet’s environmental issues. I’m always open to discuss ideas and collaborate in this growing field!

🔬 My Research

My research lies at the intersection of bioengineering, structural biology, and machine learning. My long-term goal is to contribute to creating a circular bio-economy, and I believe synthetic biology is the key to a greener future.
Currently, I’m working on several projects, including:

Sustainable Proteins: Applying AI to develop alternative food proteins.
Protein Design: Using in-silico directed evolution to improve protein functionality.
Promoter Prediction: Optimising neural network models for bacterial promoter prediction.
WASP: Developed a pipeline for protein functional annotation based on AlphaFold structural models.

I’m passionate about advancing these fields and always open to discussing ideas and collaborating with new colleagues!

Projects

WASP

Genome Annotation

WASP

A python-based software designed for comprehensive organism annotation at the whole-proteome level based on structural homology.

Jul 10, 2024

Modelling Intra-Axonal Heterogeneity

Computational Neuroscience

Modelling Intra-Axonal Heterogeneity

Investigating the impact of myelination variations along a single axon on action potential (AP) conduction. Summary Background Myelination is crucial for rapid and efficient nerve signal propagation. Traditional models assume uniform myelination, but recent findings suggest significant variability along axons.

Jul 1, 2022

Sounds Classification in the Brainstem

Machine Learning

Sounds Classification in the Brainstem

Evaluating various ML methods in classifying sound categories based on fMRI data from brainstem regions. Summary Background The auditory system processes sound through several neuronal structures, with increasing complexity as the signal moves from the cochlea to the auditory cortex.

Jun 3, 2022

Isobutanol Tolerance in S. cerevisiae

Network Biology

Isobutanol Tolerance in S. cerevisiae

Investigating pathways associated with isobutanol tolerance in S. cerevisiae to enhance biofuel production. Summary Background The research focuses on identifying pathways associated with isobutanol tolerance in the yeast strain Saccharomyces cerevisiae.

Jun 1, 2022

MAGNET_GX

Transcriptomics

MAGNET_GX

RNA-sequencing dataset analysis and metabolic pathway analysis of patients with dilated cardiomyopathy. Summary Background Dilated cardiomyopathy (DCM) is a heart condition characterised by dilation of the left or both ventricles, resulting in a weakened heart muscle and reduced pumping ability.

Feb 1, 2022

Publications

Del Missier, Shabestary, Ledesma-Amaro (2024). WASP: A pipeline for functional annotation based on AlphaFold structural models.