As part of the Imaging ONEWORLD series, the focus of these lectures is on microscopy and image analysis methods and how to apply these to your research. Almost all aspects of imaging such as sample preparation, labelling strategies, experimental workflows, ‘how-to’ image and analyse, as well as facilitating collaborations and inspiring new scientific ideas will be covered. Speakers will be available for questions and answers. The organisers, core facility staff from the University of Cambridge, Gurdon Institute, MRC-LMB and the ICR/Royal Marsden Trust are also able to continue the discussion and provide advice on your imaging projects.
Stefanie Reichelt, PhD has been head of the light microscopy facility at the CRUK Cambridge Institute. The core provides state-of-the-art imaging resources, training courses for scientists and students and develop new imaging systems as well as user-friendly analysis and acquisition tools for specific research applications. Stefanie is now Public Engagement Manager for the Biomedical Schools and teaches academically at Cambridge University, in scientific workshops and out-reach events. (http://cargocollective.com/StefanieReichelt)
Dr Alessandro Esposito obtained a PhD in Biophysics in 2006 working at the University of Utrecht and the European Neuroscience Institute in Goettingen for which he was awarded the ‘Sergio Ciani’ award by the Italian Society of Pure and Applied Biophysics. At the University of Cambridge, he then developed novel analytical tools contributing to redefining models of red blood cells homeostasis infected by P. falciparum (malaria). In recognition of his early work, in 2009 Alessandro was awarded a Life Science Interface fellowship by the EPSRC to establish foster the development of heavily multiplexed biochemical imaging. Soon after he moved to the MRC Cancer Unit where he lead the ‘Systems Microscopy initiative’ and retrained in cancer biology. During these years, Alessandro’s work developed into two research streams: i) the study of cellular responses to DNA damage and mutations in signalling pathways and ii) the innovation of biochemical imaging technologies. His team contributed to revealing the vast cell-to-cell variability in stress responses of genetically identical cells, a feature of biological systems that hinder the efficacy of disease management and therapeutic efficacy. Since 2019, Alessandro leads a transdisciplinary research programme at the MRC Cancer Unit in Cambridge devoted to understanding how DNA damage and mutations in KRAS derange homeostatic programmes leading to cancer. His group combines multi-omics data with single-cell biochemical imaging techniques aiming to achieve a deeper understanding of cancer phenotypes during the earliest stages of carcinogenesis, with particular attention to cell-to-cell variability of non-genetic origin and cell-to-cell communication.
An optical physicist and specialist in light microscopy and head of the Light Microscopy facility at the MRC Laboratory of Molecular Biology, University of Cambridge.
Kirti Prakash is a computer scientist by training (Bachelors and Masters degree) but a biologist at heart (PhD degree). Kirti aspires to be an inventor and develop new imaging tools for cell biology and neuroscience. Kirti did his Masters in Computer Science from Aalto University (Finland) and PhD in Biology from Heidelberg University (Germany). During his PhD, he developed a new method to image DNA which led to the first high-resolution images of the epigenetic landscape of meiotic chromosomes and mechanisms behind chromosome condensation. The doctoral research earned him several awards including Springer Best PhD Thesis Prize. After his PhD, he did a couple of postdocs at Carnegie Institution for Science (USA) and University of Cambridge (UK). The primary highlights of his research here were laser-free superresolution microscopy and development of a high-content imaging pipeline to quantify single-cell gene expression. Formerly at the National Physical Laboratory (NPL), and currently working at the Institute for Cancer Research (ICR) and Royal Marsden Trust, he is working on microscope development and image analysis.
Deep learning-based approaches are revolutionizing imaging-driven scientific research. In image reconstruction and classification, in segmentation and artificial labelling, they have pushed both flagship projects and bread-and-butter everyday tasks, allowing image analysis to keep pace with the recent advancements in imaging technology and instrumentation. I will talk about the recent work of my group on large-scale segmentation and exploration of cells as well as our current efforts to reduce the annotation budget for training of segmentation algorithms. I will also show how we strive to make our methods accessible to biologists without computational expertise through our software ilastik and through the emerging community network collection at the BioImage Model Zoo.
EMBL Heidelberg, Germany,
Anna Kreshuk joined EMBL in July 2018 as a Group Leader in the Cell Biology and Biophysics Unit. Her research focuses on machine learning-based methods for the analysis of biological images. Right now, she is especially interested in large-scale image and volume segmentation, sparse or weak supervision, exploitation of biological priors and, in general, in making deep learning-based segmentation methods less demanding to the amount and quality of training data. Anna is leading the development of the ilastik software, aiming to make such methods available to life scientists without computational expertise. The ilastik team is part of the collaboration behind the BioImage Model Zoo initiative, aiming to make deep learning models for microscopy interoperable and easy to share.