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07-05-2025 | Seminar

Mendelian Randomization: the past, present and future of genetic approaches to understanding phenotypic causation

<p><p><strong>Abstract</strong><br><span style="color:rgb(0,0,0);">“Mendelian randomization” (MR) is an approach that uses the special properties of germline genetic variation to help establish how an exposure phenotype influences an outcome phenotype. The recent exponential growth in the use of MR reflects the rapid expansion in data that are available for conducting such studies. This talk will take a long view on the relationship between genetics and phenotypic causation, cognisant of the fact that since natural selection is through phenotype the issue of phenotypic causality has been central to evolutionary and genetic thought in their modern formulations. Emphasis will be on the fact that for making inferences on phenotypic causality – both in epidemiological and evolutionary settings – the key assumption is of gene-environmental equivalence. The evolution of MR over the past 2 decades will be reviewed and what it can – and importantly cannot – do affirmed, and speculations about its future advanced.</span></p><p><strong>About the speaker</strong><br><span style="color:rgb(0,0,0);">Professor George Davey Smith FRS, FRCP, FMedSci is a clinical epidemiologist and the director of the MRC Integrative Epidemiology Unit (IEU) at the Bristol Medical School, University of Bristol. His research has pioneered approaches to causal inference in population health science, including developing and applying Mendelian randomization approaches. He is currently Scientific Director of the Avon Longitudinal Study of Parents and Children.</span></p></p>

15-05-2025 | Seminar

Population Dynamics: From Bacteria to Humans

<p><p><strong>Abstract</strong><br><span style="color:black;">In the last hundred years the human population and its energetic burden on the planet grew super exponentially. Yet, the global population is projected to begin declining rapidly in less than a generation. Humanity must prepare for the coming deceleration. I will discuss how microbes offer alternative models for re-imagining urban and planetary futures.</span></p><p><strong>Connection details</strong><br><strong>Zoom*</strong>: <a href="<a href="https://embl-org.zoom.us/j/92270281662?pwd=TVLvDbIDQYftgICCCXvdB8fbRi5Amy.1"><span">https://embl-org.zoom.us/j/92270281662?pwd=TVLvDbIDQYftgICCCXvdB8fbRi5A…</a> style="background-color:inherit;"><span lang="EN-US" dir="ltr"><a href="https://embl-org.zoom.us/j/92270281662?pwd=TVLvDbIDQYftgICCCXvdB8fbRi5Amy.1</span></span></a></p><p><span">https://embl-org.zoom.us/j/92270281662?pwd=TVLvDbIDQYftgICCCXvdB8fbRi5A…</a> style="color:rgb(0,0,0);">Meeting ID: 922 7028 1662 Passcode: 007635</span></p><p>Please note that the talk will <strong>not</strong> be recorded.<br><i>*For the FAQ section, as a zoom participant, please use either the chat function (the host will read out your question) <u>or</u> the “raise your hand” function and turn on your microphone.</i></p></p>

02-07-2025 | Webinar

A journey to FAIR bioimage data

<p><p><span>Bioimaging is a pervasive and indispensable methodological approach in the life and biomedical sciences. Due to the development of new technologies and the easier access to compute resources, bioimaging experiments have become a big data discipline, facing the same challenges as other omics technologies within the life sciences. However, to fully exploit the potential of bioimage data, it is necessary to make the data FAIR. In this webinar we will present viable solutions for storing, processing, analysing, and, first and foremost, sharing bioimaging data. We will introduce services provided to the scientific community, that are dealing with various aspects of the bioimage data life cycle such as:</span></p><p><span>- Where to get support for bioimage data management</span><br><span>- Local bioimage data management: OMERO and beyond</span><br><span>- Annotation of bioimage data: metadata, ontologies, REMBI etc</span><br><span>- Linking your image data with experimental protocols and analysis results</span><br><span>- Large data living in the cloud: ome.zarr</span><br><span>- Publication of bioimage data</span></p></p>

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