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Posts

portfolio

publications

Challenges of analysing stochastic gene expression in bacteria using single-cell time-lapse experiments

Published in Essays in Biochemistry, 2021

Here we look at the issues surrounding measurement of single-cell gene expression in bacteria growing in microfluidic devices such as the mother machine.

Recommended citation: Hardo, Georgeos., Bakshi, Somenath. (2021). "Challenges of analysing stochastic gene expression in bacteria using single-cell time-lapse experiments." Essays in Biochemistry. 65(1).
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Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks

Published in BMC Biology, 2022

A tool to generate synthetic training data of bacteria under the microscope to train highly accurate and precise segmentation and tracking models.

Recommended citation: Hardo, Georgeos., et al. (2022). "Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks." BMC Biology. 20, 263.
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Quantitative microbiology with widefield microscopy: navigating optical artefacts for accurate interpretations

Published in npj Imaging, 2024

Analysing optical artefacts affecting quantification of single-cell parameters using virtual microscopy and bioimage analysis of targetted experiments.

Recommended citation: Hardo, Georgeos., et al. (2024). "Quantitative microbiology with widefield microscopy: navigating optical artefacts for accurate interpretations." npj Imaging
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talks

teaching

Mathematical Biology - Natural Sciences Tripos

Undergraduate course, Corpus Christi, Pembroke, and St Catherine's Colleges - University of Cambridge, 2020

Supervised this course from 2020-2023. A year-long mathematics course for undergraduates, encompassing a quarter of their teaching time in the first year. Taught probability theory, linear algebra, probability theory, statistics, linear models, calculus, differential equations, biological systems modelling.

BioDesign - MPhil Computational Biology

Graduate course, Department of Applied Mathematics and Theoretical Physics - University of Cambridge, 2022

Supervised this course from 2022-2024. The course introduces practical techniques for biodesign. These have originated in the molecular techniques that have become ubiquitous in modern biology. Combined with the growing understanding of biology, we are now able to adapt existing biological systems within cells, or design non-living systems that make use of biological molecules.

Cambridge iGEM 2022

Student competition, Department of Engineering - University of Cambridge, 2022

Instructed the Cambridge team for the 2022 iGEM (International Genetically Engineered Machine) competition. The team designed, modeled, and constructed an integral controller for synthetic genetic circuits, aiming to enhance robustness in metabolic engineering applications. The team’s success led to their winning a gold medal at the final competition.

Part III Systems Biology

Graduate course, Cambridge Systems Biology Centre - University of Cambridge, 2022

Supervised this course from 2022-2024. An advanced and mathematics focussed 4th year undergraduate/graduate course for the top performers of the Cambridge Natural Sciences Tripos. Taught evolutionary modelling, stochastic modelling of gene expression, synthetic biology principles, bioinformatics, game theory.

Cambridge iGEM 2023

Student competition, Department of Chemical Engineering and Biotechnology - University of Cambridge, 2023

Instructed the Cambridge team for the 2023 iGEM (International Genetically Engineered Machine) competition. The team engineered Bacillus subtilis to form protective biofilms capable of preventing the colonization of harmful bacteria and, for agricultural applications, designed a biosensor for pathogenic biofilm detection. This led the team to win their second gold medal at the final competition.

Cambridge iGEM 2024

Student competition, Department of Chemical Engineering and Biotechnology - University of Cambridge, 2024

Instructed the Cambridge team for the 2023 iGEM (International Genetically Engineered Machine) competition. The team developed a novel magnetogenetic system for spatiotemporal gene expression control by designing magnet-inducible AND gates and creating open-source hardware (MagentaBOX) for localized magnetic stimulation. This led the team to win their third gold medal in a row at the final competition.