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Florian Levet

Publications and source records attributed to Florian Levet.

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GloBIAS: strengthening the foundations of BioImage Analysis

There is a global need for BioImage Analysis (BIA) as advances in life sciences increasingly rely on cutting-edge imaging systems that have dramatically expanded the complexity and dimensionality of biological images. Turning these data into scientific discoveries requires people with effective data management skills and knowledge of state-of-the-art image processing and data analysis, in other words, BioImage Analysts. The Global BioImage Analysts' Society (GloBIAS) aims to enhance the profile of BioImage Analysts as a key role in science and research. Its vision encompasses fostering a global network, democratising access to BIA by providing educational resources tailored to various proficiency levels and disciplines, while also establishing guidelines for BIA courses. By collaboratively shaping the education of BioImage Analysts, GloBIAS aims to unlock the full potential of BIA in advancing life science research and to consolidate BIA as a career path. To better understand the needs and geographical representation of the BIA community, a worldwide survey was conducted and 291 responses were collected across people from all career stages and continents. This work discusses how GloBIAS aims to address community-identified shortcomings in work environment, funding, and scientific activities. The survey underscores a strong interest from the BIA community in activities proposed by GloBIAS and their interest to actively contribute. With 72% of respondents willing to pay for membership, the community's enthusiasm for both online and in-person events is set to drive the growth and sustainability of GloBIAS.

physics.bio-ph

Bio-Image Informatics Index BIII: A unique database of image analysis tools and workflows for and by the bioimaging community

Bio image analysis has recently become one keystone of biological research but biologists tend to get lost in a plethora of available software and the way to adjust available tools to their own image analysis problem. We present BIII, BioImage Informatic Index (www.biii.eu), the result of the first large community effort to bridge the communities of algorithm and software developers, bioimage analysts and biologists, under the form of a web-based knowledge database crowdsourced by these communities. Software tools (> 1300), image databases for benchmarking (>20) and training materials (>70) for bio image analysis are referenced and curated following standards constructed by the community and then reaching a broader audience. Software tools are organized as full protocol of analysis (workflow), specific brick (component) to construct a workflow, or software platform or library (collection). They are described using Edam Bio Imaging, which is iteratively defined using this website. All entries are exposed following FAIR principles and accessible for other usage.

q-bio.QM

Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

Surface molecules, distributed in diverse patterns and clusters on cell membranes, influence vital functions of living cells. It is therefore important to understand their molecular surface organisation under different physiological and pathological conditions. Here, we present a model-free, quantitative method to determine the distribution of cell surface molecules based on TIRF illumination and super-resolution optical fluctuation imaging (SOFI). This SOFI-based approach is robust towards single emitter multiple-blinking events, high labelling densities and high blinking rates. In SOFI, the molecular density is not based on counting events, but results as an intrinsic property due to the correlation of the intensity fluctuations. The effectiveness and robustness of the method was validated using simulated data, as well as experimental data investigating the impact of palmitoylation on CD4 protein nanoscale distribution in the plasma membrane of resting T cells.

physics.bio-ph