Big data methods for electric functional scanning probe microscopies in Biology

Group: Nanoscale bioelectric characterization
Group leader: Gabriel Gomila (

The passive electrical properties of biological systems, such as the electric charge, conductivity or electrical polarization play a fundamental role in several physiological processes such as cellular communication, adherence to surfaces, internalization of nutrients, molecules or particles and cellular growth. Due to this relevance, several techniques have been developed along the years to probe the electrical properties in biological systems. However, in most cases, these techniques only provide a spatial resolution in the micrometer range, what does not allow accessing the very local electrical properties at the nanoscale, which are fundamental in most electrophysiological phenomena. To address these properties at this scale specific innovative methods are required to acquire, process and analyze huge volume of data. The objective of the present project is to develop big data methods, including machine learning methods, adapted to electric scanning probe microscopes, to produce the first electrical functional images of living cells at high spatial resolution (sub-100 nm).

Checa, Marti, Millán, Rubén, Blanco, Núria, Torrents, Eduard, Fabregas, Rene, Gomila, Gabriel, (2019). Mapping the dielectric constant of a single bacterial cell at the nanoscale with scanning dielectric force volume microscopy Nanoscale 11, 20809-20819