Topic: quality control

This course develops a metabolomics investigation from experimental design through data preparation and statistical interpretation. Lectures, practical work and group discussion connect analytical chemistry and data collection with reproducible analysis. Exercises cover R data handling and visualisation, xcms processing of untargeted mass-spectrometry data, quality control, missing values and compound annotation. The final module compares univariate tests, multiple-testing correction, principal-component methods, partial least squares and random forests for metabolomic matrices. Sessions: 16,

Analyze gene expression within tissue using imaging-based and sequencing-based spatial transcriptomics. Guided R/Bioconductor labs cover cell segmentation, quality control, interactive exploration and integration with single-cell datasets. Downstream analyses characterize cellular niches, neighbourhoods and cell–cell communication. The course concludes with project design and a team hackathon using participant or public data, connecting computational outputs to biological interpretation. 2026-12-14–2026-12-18, 14:00–18:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €530. Designe

This feasibility-study competition supports collaborative projects that accelerate and commercialise battery technologies, respond to a specific sector and market demand, remove industry hurdles and strengthen the UK battery value chain. In-scope work includes materials extraction and processing, cell and pack technologies, manufacturing tools, quality control, diagnostics, testing, simulation and digital tools. Projects must request £70,000 to £500,000, last 6 to 18 months, start no earlier than 1 May 2027 and finish by 31 March 2031. The competition closes on 2 December 2026 at 11:00am UK ti

In this talk, I will discuss the OpenNeuro Fitlins GLM package and provide an illustration of the analytic workflow. OpenNeuro FitLins GLM is a semi-automated pipeline that reduces barriers to analyzing task-based fMRI data from OpenNeuro's 600+ task datasets. Created for psychology, psychiatry and cognitive neuroscience researchers without extensive computational expertise, this tool automates what is largely a manual process and compilation of in-house scripts for data retrieval, validation, quality control, statistical modeling and reporting that, in some cases, may require weeks of effort.