Automated Machine Learning Pipeline to classify cell behaviour and phenotype based on endogenous and exogenous biosensor probes readouts

Objectives

1. To train the DC in theory of python coding and application of appropriate machine learning approaches in preparing a classification algorithm based on multiparametric input and output data.

2. Apply machine learning classification to human macrophages stimulated towards two contrasting phenotypes DC will establish a semi-automated system whereby any data file containing FLIM data; (FLIM algorithm library that supports the most popular FLIM file formats and can be utilized and modified easily by a developer;) that will ultimately present as a intuitive FLIM analysis tool that uses the library and yet still can be used easily and directly by the bench biologist; and the integration of FLIM analysis with versatile microscopy image analysis.

3. While working on their own application (that being the model of macrophage polarisation); the DC will engage with other DCs in adjusting the pipeline to the analysis of data and additional sensor readouts.

Host Academic Institution: Trinity College Dublin