29 September 2022

Poster prizes for the Matthäus group at the European Conference for Mathematical and Theoretical Biology

iMOL is proud to announce that PhD students of the Matthäus group have been awarded prizes at this year’s ECMTB 2022 in Heidelberg, a major conference with 750 participants. Marc Pereyra received the Lewis Wolpert Best Poster award. This prize is awarded annually for outstanding contributions to the field of theoretical biology. Marc’s poster can be viewed here. Zoë Lange won the ECMTB award for the best poster in developmental biology’. Her poster can be viewed here. Gustavo Hernandez-Mejia’s received the ECMTB award for the best poster in epidemiology. His poster can be viewed here.

The happy awardees: Marc Pereyra (left), Gustavo Hernandez-Mejia (center) and Zoë Lange (right) (photo by Camile Fraga Delfino Kunz)

28 September 2022

Fast DNA-PAINT imaging using a deep neural network

The advent of super-resolution imaging has overcome the diffraction-limited barrier of light microscopy into obtaining images at nanometre spatial resolution. DNA-PAINT (short for “DNA points accumulation for imaging in nanoscale topography”) is a super-resolution technique with relatively easy-to-implement multi-target imaging. However, image acquisition is slow as sufficient statistical data has to be generated from spatio-temporally isolated single emitters. iMOL scientists and colleagues have trained the neural network DeepSTORM to predict fluorophore positions from high emitter density DNA-PAINT data. They report in the journal Nature Communications that they achieved this way image acquisition in one minute. They demonstrate multi-colour super-resolution imaging of structure-conserved semi-thin neuronal tissue and imaging of large samples. This improvement can be integrated into any single-molecule imaging modality to enable fast single-molecule super-resolution microscopy.

Research paper: Kaarjel Narayanasamy, Johanna Rahm, Siddharth Tourani and Mike Heilemann (2022) Fast DNA-PAINT imaging using a deep neural network. Nature Communications 13: 5047. Link

Contact: Mike Heilemann, Institute of Physical and Theoretical Chemistry, Goethe University, Frankfurt/Main, heileman@chemie.uni-frankfurt.de