Computational Biology workshops

Assemble eukaryotic genomes by combining long-read sequencing with chromatin-contact data. Practical work progresses from read manipulation and k-mer analysis through assembly algorithms, removal of duplicated haplotigs and Hi-C scaffolding. Participants assess contiguity, sequence accuracy and gene completeness with approaches including Merqury and BUSCO, and finish by comparing results from small eukaryotic datasets. The theoretical component explains how repeats, heterozygosity and sequencing technologies influence assembly choices. Sessions: 9–13 November, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €530. Suitable for researchers learning de novo assembly, including beginners; Linux practice is included. An optional €900 bundle includes the separate manual-curation course.

Quantify biological shape through a reproducible three-dimensional morphometrics workflow in 3D Slicer and R. Participants connect image acquisition and resolution to segmentation and cleaning, collect landmarks and semilandmarks, and derive shape variables using Procrustes alignment and sliding procedures. Statistical exercises use principal components and regression to interpret size and shape variation; visualisations include deformations, morphings and heatmaps. Live sessions: 9–13 November, 13:00–18:00 daily, Europe/Madrid (CET, UTC+01:00). Total 30 hours: 25 live plus five independent. English-language live online course; Fee €610; Ambassador Institution rate €488. VAT included. Capacity: 20. A Life Sciences degree and familiarity with R and geometric-morphometric concepts are expected. R/RStudio and 3D Slicer are required. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

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.

The second M4H workshop brings mathematics, data science and medical research together to improve care. Mathematical models, numerical methods, statistics and machine learning support precision medicine, healthcare-resource allocation and multimodal patient-data analysis. Keynotes examine evolutionary cancer treatment and model-driven digital twins, longitudinal health records, topology and geometry for cyclic gene expression, statistical approaches to individual mental-health variation and patient-specific blood-flow simulation. Panels connect these methods with cardiovascular medicine, health data science and sustainable brain health. The Department of Mathematics at Politecnico di Milano hosts the in-person workshop on 11–13 November 2026 in Aula Rogers, Building 11, Via Ampère 2, Milan. Posters use Aula Vetrata, Trifoglio Building 13, Via Bonardi 9. The programme runs 11 November 14:00–19:30, 12 November 09:00–18:10 and 13 November 09:00–16:00. Times are Europe/Rome, CET (UTC+01:00). Registration is free and open until 15 October through the form on the official workshop page. Speaking slots are invitation only; general attendance is open, and participants may submit poster abstracts.

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.

Use Hi-C contact maps to diagnose and correct assembly errors and produce chromosome-scale genome sequences. The workflow starts with assembly metrics and contamination screening, then constructs PretextView maps and supporting tracks and applies a rapid-curation pipeline to generate corrected FASTA files. Exercises address repeats, haplotype duplication and phasing, microchromosomes, polyploid genomes and sex-chromosome identification. Group work culminates in evaluating and discussing difficult assemblies. Sessions: 16–20 November, 14:00–18:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €480. Biological background is expected. Unix command-line skills are mandatory for running scripts; previous assembly experience is helpful. An optional €900 bundle includes the separate genome-assembly course.

A five-day practical course for experimentalists and computational biologists analysing single-cell RNA sequencing. Lectures and exercises follow data from sequencing files to expression matrices, quality control, normalisation, batch correction, dimensionality reduction, clustering, annotation and differential expression. Later sessions cover trajectory and pseudotime inference, RNA velocity, single-cell multi-omics integration and functional analysis. Participants finish with an independent dataset analysis and presentation. Bash and R/Bioconductor support reproducible workflows and interpretation. Online, 16–20 November 2026, 14:00–20:00 CET (Europe/Berlin) each day. Fee: €530. Participants need practical Unix command-line skills, R programming experience and familiarity with next-generation sequencing analysis.

Genomics, proteomics and imaging now measure molecules and cells across many scales. This workshop examines how mechanistic models can integrate those measurements and biological dynamics to explain and engineer cellular behaviour. Researchers in single-cell analysis, dynamic proteomics, quantitative imaging, synthetic biology and theory will connect experimental and computational approaches. The programme links three themes: cell dynamics and interactions; molecular mechanisms and engineering; and rigorous quantitative models. Sessions address multiscale modelling, molecules over time, large-scale perturbations, prediction of cell states, dynamic processes, and stem-cell engineering. Virtual participation includes livestreamed talks, questions and discussion, plus available recordings for four weeks; individual speakers may decline recording. Virtual participants cannot submit presentation abstracts. Fees: PhD students €175, academia €200, industry €275; card payment is required. Virtual registration closes 10 November 2026. On-site registration is closed. Programme times are Europe/Berlin (CET, UTC+1): 17 November opening at 13:15 and talks from 13:30; 18 and 19 November sessions from 09:00; 20 November from 10:00, with closing remarks at 13:15–13:30.

A five-day research workshop combines molecular simulations and AI-assisted drug discovery with practical hacking sessions and direct mentoring. Training covers enhanced sampling, QM/MM simulation and free-energy calculations, with discussion of current computational research workflows. The meeting brings together forty participants spanning master’s students, doctoral researchers, postdoctoral researchers and faculty, alongside invited experts from Europe, the United States and South America. Activities take place at Universidad de los Andes and Universidad Nacional de Colombia in Bogotá. Pre-registration is first come, first served through 20 October; the local organizer lists a COP 95,000 fee including four lunches and separate travel/accommodation scholarship support.

Build a small-RNA analysis workflow from raw reads to curated microRNA annotations. Participants assess sequencing quality with miRTrace, retrieve public datasets and reproduce analyses and figures from published studies. Practical work combines MirMachine, miRTrace and MirMiner with genomic context and annotation standards, then examines false positives and missing genes through manual curation. The emphasis is on defensible identification of regulatory microRNAs and critical assessment of published predictions. Sessions: 23–26 November, 12:00–17:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €480. Basic small-RNA biology and genomics, Unix/Linux shell and conda familiarity are expected.

Build and evaluate deep-learning models for biological prediction using Python and Jupyter notebooks. Lectures and collaborative exercises develop convolutional networks for classification, regression and image segmentation, with attention to preprocessing, augmentation, class imbalance, cross-validation and overfitting. Later sessions explore learning-rate and training-duration choices, recurrent networks and applications to omics data. Participants interpret model performance and discuss their own research problems. 2026-11-23–2026-11-27, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €530. A biology background is expected; basic Python and Linux familiarity is helpful but not required.

Analyse microbial communities from shotgun sequencing using reproducible computational workflows. The workshop covers read preprocessing, taxonomic and strain-level profiling, functional characterisation, metagenome assembly and reconstruction of microbial genomes. Exercises use tools including MetaPhlAn, StrainPhlAn, PanPhlAn, HUMAnN, MEGAHIT and PhyloPhlAn, while comparing short- and long-read approaches. Statistical sessions address community diversity, high-dimensional testing, regression and classification, followed by visualisation and reusable scientific reports. Live online, 23–26 November, 14:00–20:00 Europe/Berlin (CET). Fee €530. Basic command-line knowledge is helpful; preparatory Unix material is provided.

This live course introduces sequencing-data analysis through a real Illumina dataset. It explains how sequencing technologies affect data quality and interpretation, then develops the Linux and file-format skills needed for practical analysis. Exercises cover quality control, adapter removal, read mapping, alignment statistics, genome-browser visualization, DNA variant calling, VCF filtering and interpretation. Participants compare analytical tools and learn to recognize errors that can affect biological conclusions. The online sessions run 09:00–17:00 CET (UTC+1) on 23–25 November 2026. The course is taught in English for biologists and data analysts with basic molecular-biology knowledge; prior Linux experience is unnecessary. A computer, current browser and audio equipment are required. Exercises use a supplied cloud computer through the browser. The fee is EUR 879 excluding VAT and includes printed materials and cloud access. Capacity is 25, with places subject to confirmation and a waiting list if full. Registration closes on 22 November. Sessions are live and build sequentially, so continuous attendance is expected.

Create interactive, reproducible views of omics datasets with the iSEE Bioconductor framework. Participants configure linked panels, inspect bulk and single-cell RNA data and preserve exploratory workflows. Guided cookbook exercises progress to independent exploration, collections of datasets and participants’ own projects, with troubleshooting and companion-package demonstrations. The framework also supports spatial and proteomic data represented by SummarizedExperiment objects. Sessions: 25–26 November, 13:00–17:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €280. For advanced MSc, doctoral and postdoctoral researchers. Familiarity with sequencing data, common single-cell data containers and visualisation is helpful.

Develop Bayesian analyses of biological data from prior specification and posterior estimation to computational diagnostics and multimodal integration. Practical work covers conjugate and non-conjugate models, Gibbs and Hamiltonian Monte Carlo, convergence checks, hierarchical regression, regularisation and variational inference. Later sessions compare data-fusion strategies and Bayesian factor models while quantifying uncertainty in integrated biomedical datasets. Sessions: 30 November–4 December, 14:00–18:00 daily, Europe/Berlin (CET, UTC+01:00), with Slack discussion between meetings. Live online training; fee €480. For advanced MSc, doctoral and postdoctoral researchers with R/Bioconductor, probability, statistics and regression experience.

Detect and interpret genomic alterations of at least 50 bases using short and long reads. Lectures and practical exercises compare assembly-based and reference-mapping workflows, evaluate sequencing and assembly quality, and filter and annotate structural variants. Participants build trio or population VCF datasets, examine mosaic and somatic variation, and prioritise possible functional effects using human-genome examples. Linux and cloud exercises connect raw data processing with interpretation of disease and phenotype associations. Sessions: 30 November–2 December, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €450. A biology background and familiarity with genomic data formats are expected. Command-line Linux practical work is introduced during the course.

Reconstruct evolutionary trees while representing prior knowledge and uncertainty in BEAST2. Lectures and tutorials explain prior selection, birth–death and coalescent models, fossil information, multispecies coalescence and rate variation across clades. Participants compare models and troubleshoot practical analyses, with time to develop their own datasets. The emphasis is on choosing and diagnosing complex models rather than treating software settings as a black box. Live Zoom sessions: 30 November; 2, 4, 7, 9 and 11 December, 15:00–18:30, Europe/Madrid (CET, UTC+01:00). Total 35 hours: 21 live plus 14 independent, with Slack-supported tasks. English-language live online course; Fee €680; Ambassador Institution rate €544. VAT included. Capacity: 20. A Biology degree, or palaeontological background, and familiarity with Bayesian phylogenetics are expected; an introductory video series can supply the prerequisite. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

Apply machine learning throughout drug discovery, from biological target identification to molecular screening. The workshop explains model design, training, evaluation and prediction interpretation, then develops deep-learning and graph-neural-network methods in PyTorch. Practical work turns molecular and omics data into model inputs, implements a graph model from a scientific paper, and examines disease classification and target discovery. The final day builds pipelines from research databases and introduces language-model fine-tuning using biological data. Live online, 30 November–3 December, 14:00–19:00 Europe/Berlin (CET). Fee €480. Aimed at MSc/PhD students and early-career scientists, with basic Python, molecular biology, chemistry and data-analysis knowledge. Previous machine-learning experience is unnecessary.

Infer evolutionary relationships and divergence times from multilocus genomic data while accounting for sources of misleading phylogenetic signal. The workshop examines orthologue selection, sequence-evolution models and discordance caused by incomplete lineage sorting and introgression. Lectures and hands-on exercises develop time-calibrated phylogenies and compare the assumptions of alternative inference methods. Analyses run in a prepared cloud environment so participants can concentrate on statistical methods, model choices and interpretation. Live online, 30 November–4 December, 12:00–18:00 Europe/Berlin (CET). Fee €530. Intended for PhD and postdoctoral researchers planning multilocus phylogenetic studies. Basic Unix command-line knowledge is required; familiarity with scripting is useful.

This practical workshop trains structural biologists in cryoelectron tomography and subtomogram averaging using nextPYP, TomoBEAR and Warp/M, with teaching by the software developers. It follows the processing pipeline from tilt-series alignment and reconstruction through tomogram visualisation and archiving, manual and automated particle picking, extraction, subtomogram alignment and averaging, refinement and classification. Participants will build averaging projects and create three-dimensional maps. The workshop begins at 09:00 on 2 December and ends at 15:00 on 4 December 2026, Stockholm time (CET, UTC+1). No previous experience is required; bring a laptop and mouse. Selection considers applicants’ research projects and plans, with priority for current cryoET researchers and SciLifeLab cryo-EM facility users. Submit an application letter and CV by 23 October at 16:00; decisions are expected by 2 November, and payment is due 20 November. Fees are SEK 1,600 for academic participants and SEK 4,800 for industry. They cover three days of teaching, materials, lunches, refreshments, a certificate and the second-night dinner; travel and accommodation are additional.