PhD Student

Kate Kilgour
Kate Kilgour
Scottish Flag
Kate Kilgour

Project Description

I joined the Lamond Laboratory in 2018 to undertake a computational PhD, funded by the Medical Research Council.

My research focuses on investigating how modern machine-learning techniques can enhance the results of mass spectrometry-based proteomics. One of the biggest challenges in doing so, is navigating the “high dimensional, small sample size” problem which is common in ‘omics fields. My project focuses on dimensionality reduction aspects of deep learning which aim to maximise the signal extracted from the data, whilst minimising the number of variables required to characterise said signal.

PepTracker provides management and mining capabilities for data generated during mass spectrometry studies.
Data Shop
Visualisation and statistical analysis tool for quantitative datasets
Proteomics Support
The Proteomics Support team have created a website that provides useful resources for proteomics studies.
Encyclopedia of Proteome Dynamics
A collection of multi-dimensional proteome properties from large-scale mass spectrometry experiments
Cell Biologist's Guide
The Cell Biologist's Guide to Proteomics provides information about mass spectrometry and experimentation.