Analytical Chemistry workshops

This hands-on course analyses mass-spectrometry measurements of biochemically fractionated cells to infer subcellular protein locations. Participants build reproducible R/Bioconductor workflows for preprocessing, quality assessment, annotation and machine-learning-based localization prediction. Guided examples connect protein profiling measurements to cellular maps and interpretation. The course targets proteomics researchers, bioinformaticians and data analysts; previous proteomics experience is helpful but introductory experimental context is provided. It covers fractionation-based measurements rather than antibody imaging or other spatial microscopy technologies. The dated programme lists online teaching from 12:00 to 16:00 Berlin time on November 10–12.

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, 17, 18 and 20 November, 09:30–13:30, Europe/Berlin (CET, UTC+01:00); no session on 19 November. Live online training; fee €480. Familiarity with R is assumed; prior metabolomics experience is useful.

Work through mass-spectrometry proteomics analysis in R and Bioconductor, from raw observations to statistical interpretation. Practical tutorials cover data formats, extraction and visualization, integration of identification results, quantitative data structures and preprocessing. The final session uses statistical analysis to identify proteins with different abundance between experimental groups. 2027-01-27–2027-01-29, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €380. Working R knowledge is required. Mass-spectrometry or proteomics familiarity is useful but not essential; typical datasets and instruments are introduced during the course.

This hands-on course focuses on analysing, interpreting and statistically evaluating quantitative proteomics data. Researchers with basic mass-spectrometry knowledge learn how stable-isotope labelling and label-free approaches support biological experiments, and how to select suitable hardware, software and analysis strategies. Computer-based practicals and group exercises develop skills for handling quantitative data, while lectures connect protein regulation, cellular communication, functional and chemical proteomics, and post-translational modifications. A dedicated session examines practical uses of AI in proteomics and mass spectrometry. The course is relevant both to wet-lab researchers seeking computational experience and to researchers deepening their understanding of quantitative methods.

Learn metabolomics experimental design, LC-MS and imaging acquisition, quality control, data processing, compound annotation and modelling through lectures, practicals and public-data case studies. The course uses Galaxy and MetaboLights to teach standardised workflows, open data and submission practices, including lipidomics and biological interpretation. It is intended for researchers new to metabolomics; basic command-line or Galaxy familiarity helps. There are 30 selected places. Fees are £975 for academia and £1,275 for industry, including four nights’ accommodation and programme catering. Applications open 2 November 2026 and close at 23:59 UK time on 31 January 2027; decisions follow by 12 February.

The Society for Mycotoxin Research brings together research on fungal toxins, from their occurrence and management to the fungal biology, ecology and genetics that determine production. The workshop connects analytical methods with toxicology, exposure biomonitoring and approaches to remediation and mitigation. A travel-support scheme for eligible early-career scientists aged 40 or younger from designated developing countries accepts applications from November 1 through December 31, 2026; it requires a scientific contribution and supports in-person attendance.

Process mass-spectrometry proteomics data from spectra through peptide identification and quantification to protein lists and functional interpretation. Practical training covers search and post-processing tools, quantitative and data-independent methods, public-data reuse, proteogenomics, PRIDE, ProteomeXchange, UniProt and interaction resources including IntAct and IMEX. Participants need a scientific degree; familiarity with proteomics mass spectrometry is helpful. There are 30 selected places, costing £975 for academia or £1,275 for industry. Applications open 14 December 2026 and close at 23:59 UK time on 14 March 2027, with decisions by 26 March. The confirmed 12–16 July dates replace the previously advertised 5–9 July schedule.