Our paper "DeepGEEP: Data-Driven Prediction of Bacterial Biofilm Gene Expression Profiles" has been posted to bioRxiv. This paper considers petri dish experiments where a signaling molecule that can stimulate fluorescence is added to a freshly-plated bacteria sample. The fluorescence is triggered by gene expression and requires that the local signaling molecule concentration is within a suitable range. We try to predict where fluorescence will occur based on the location where the signaling molecules are dropped onto the dish. A convolutional neural network is applied to simulated data to make the predictions.

This paper is an output of the SIMBA project. It is first-authored by our group member Hamidreza Arjmandi and co-authored with Christophe Corre (University of Warwick School of Life Sciences and Department of Chemistry) and Hamidreza Jahangir.

We've made our group's first pre-print submission to bioRxiv. We posted our paper 3D Cell Cultures Amplify Diffusion Signals. This paper models the amplification of diffusion signals that occurs across the boundary of an organoid immersed in liquid. With a combination of theory and experiments, we verify the amplification factor as a function of diffusion coefficients inside and outside the organoid. The main result is that, on a very short timescale, organoids act like sponges and can make measurable changes to nutrient concentrations in the surrounding environment. This provides useful insight for lab-on-chip systems and other applications that have dense collections of cells.

This paper is an output of the SIMBA project. It is first-authored by our group member Hamidreza Arjmandi and co-authored with our SIMBA project collaborators at AstraZeneca Sweden (Kajsa Kanebratt, Liisa Vilen, and Peter Gennemark).