Advanced SMLM Colocalization, Statistical tools for analyzing spatial objects distribution [NA@Home]

In this webinar from the NEUBIAS Academy @Home series, we will first present advanced colocalization methods for analyzing SMLM data, before introducing statistical tools for analyzing the spatial distribution of objects.Part1: By generating point clouds instead of images, SMLM has necessitated the development of dedicated colocalization methods. In the first part of the webinar, we will present several density-based methods computing colocalization estimators directly from the localization coordinates.Part 2: The second part of the webinar will be dedicated to object-based colocalization methods, with a strong focus on robust statistical analysis. This analysis applies to any type of microscope image (from cryo-em and SMLM to widefield imaging), providing that the positions of the objects (molecules, cells…) can be estimated.



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Learning Outcomes:

At the end of the webinar, participants will have a good knowledge of advanced colocalization methods for analyzing SMLM data, and spatial statistics for characterizing the spatial distribution of molecular assemblies in a wide range of imaging modalities.

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Content

00:00:00 Introduction to NEUBIAS Academy
00:00:43 Introduction to the webinar

00:01:45 ADVANCED COLOCALIZATION METHODS FOR SMLM (Florian Levet)

00:40:06 Questions & Answers
00:47:39 STATISTICAL TOOLS FOR ANALYZING THE SPATIAL DISTRIBUTION OF OBJECTS (Thibault Lagache)

01:16:48 Questions & Answers


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Presenters:

Dr. Florian Levet, IINS / INSERM, Bordeaux, France.

Dr. Thibault Lagache, Institut Pasteur, Paris, France.



Moderators, Bioimage Analysts: Rocco d’Antuono (Crick Institute), Marion Louveaux (Pasteur Institute), Daniel Sage (EPFL, Lausanne), Suvadip Mukherjee (Pasteur, Paris), Lydia Danglot (Institute of Psychiatry and Neurosciences, Paris), Anna Klemm (Univ. Uppsala)


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All Questions & Answers are available on the image.sc forum, where you can further ask questions in the future:
https://forum.image.sc/t/neubias-acad...