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Dr. Alice Pyne, a leading Royce researcher recently recognised for her commitment to open science and open data, leads a team of collaborators at the University of Sheffield who have developed Topostats, a Python toolkit with an open licence.
Alice’s group have developed TopoStats which enables researchers to automate editing, analysis and quantification of Atomic Force Microscopy (AFM) images to determine the structure of materials at the nanoscale. This unique functionality aids the field in moving away from manual analysis processes which have low throughput and rely on experienced researchers. The team’s current focus is on developing new image analysis functionality for TopoStats to accelerate the development of novel therapies and improve our understanding of health and disease.
By making TopoStats open-source, they have reached new collaborators across the world in academia and industry, who are using the software to quantify materials from next-generation sustainable materials such as solar cells, to new AI-designed nanostructures for drug delivery.
Beyond specific functionality, TopoStats can be seen as a tool to drive a transformation in research culture, placing greater emphasis on open, quantitative analysis of microscopy data, and introducing strategies for standardisation and metadata capture. Alice’s team, have been recognised for this work by the inaugural Sheffield Open Research Team Prize.
High resolution AFM of DNA minicircles, as reported in Alice L. B. Pyne et al, Nature Communications, 12, Article number: 1053 (2021).
Dr. Alice Pyne is a Senior Lecturer in Polymers and Soft Matter and head of the Nanocharacterisation Laboratory at the University of Sheffield’s Royce Discovery Centre.
In 2023 she was recognised with the Royal Microscopical Society’s Atomic Force Microscopy & Scanning Probe Microscopy award for her commitment to open science and open data.
Pyne is the acknowledged leading light in the field of high-resolution imaging of DNA and DNA protein interactions, and has also been instrumental in steering the community towards a more integrated and collegiate approach to AFM image analysis.