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NMR spectroscopy is an essential and powerful technique for studying the functional structure, dynamics and interactions of biological macromolecules at atomic resolution, complementary to cryo-EM and X-ray crystallography. It is unique in providing dynamic information over a large range of time scales and thereby revealing the molecular mechanisms that control biological function. Continuous and recent developments in NMR include studying intrinsically disordered proteins and their interactions, high resolution insights into dynamics of RNA, functional dynamics in megadalton protein machines, and protein conformation and interactions in living cells, aided by new developments with machine learning, AI/DL, and new pulse sequences.The course provides essential training in modern NMR techniques, providing a solid knowledge foundation for the next-generation of NMR spectroscopists. Topics include NMR theory, pulse sequence design, data processing, structural analysis supported by AI/DL, techniques to study multi-timescale dynamics, and in-cell NMR.  An important aspect of the course is its focus on practical skills i.e. hands-on experience in setting up, processing and analyzing NMR experiments and deriving quantitative structural and dynamic information. All lectures and practicals are guided by international experts in the field. 

Conference SummarySince 1990, this important and unique conference has continued to focus on the structure, replication, and segregation of chromosomes using yeast model systems to understand genome maintenance and its link to disease. This year’s unique program will focus on the use of yeast model systems to study the structure, replication, and segregation of chromosomes, cellular states and transitions, genome maintenance and evolution, and their links to disease. The conference will bring together researchers investigating these areas, serving as a critical vehicle for the dissemination of important findings, exploration of emerging technologies, and collaborations. It will be an exceptional venue for early-career researchers to present their work and network with leading scientists in the field.Attendees will learn about:· New insights into chromosome organization, duplication, stability, and segregation.· How multi-disciplinary approaches are being used to explore cell cycle control and genome stability.· Novel genomics and high-throughput technologies developed using yeast models.· Discoveries in the evolutionary aspects of chromosome biology.Program Topics· Chromatin and nuclear organization· Cell states and transitions· Chromosome duplication· Dynamics of chromosome structure· Genome evolution· Chromosome segregation mechanisms· Cell Size Control· Telomeres · DNA damage repairWorkshopsA Meet the Experts session will provide early-career researchers an opportunity to discuss career and scientific advice with experts in the field.A Career Development Workshop will feature a panel of experts, with advice on mentorship and career trajectories.

The International Conference on Precision Medicine and AI Healthcare (HealthAI2026) will be held on July 27–28, 2026 in the vibrant city of Prague, Czech Republic. Organized by PAGES, this global gathering will unite clinicians, researchers, healthcare leaders, AI innovators, and policymakers to explore the transformative role of artificial intelligence and personalized medicine in improving patient outcomes.Why Attend HealthAI2026?HealthAI2026 offers a unique platform to showcase breakthrough research to an international audience of healthcare professionals, AI innovators, and policy leaders. Attendees will explore cutting-edge advancements in genomics, AI-powered diagnostics, digital health, and medical data science. Beyond presentations, the conference fosters meaningful global partnerships that bridge the gap between medicine, technology, and healthcare policy—driving real-world impact and shaping the future of precision medicine.HealthAI2026 provides a dynamic platform for presenting breakthrough research, discussing cutting-edge technologies, and fostering collaborations between medicine, data science, and healthcare innovation. With keynote lectures, interactive sessions, workshops, and networking opportunities, this conference is a must-attend event for anyone shaping the future of healthcare.Join us in Prague for HealthAI2026 and be part of the global movement redefining the future of healthcare through precision, innovation, and intelligence.

Course overviewBiological and biomedical research frequently employs multiple ‘omics methods(“multi-omics”) to investigate biological systems comprehensively. This approach simultaneously examines various molecular layers (DNA, RNAs, proteins, metabolites) and helps to overcome limitations inherent in individual technologies. These modalities are increasingly profiled at single-cell and/or spatial resolutions. Integrating and analysing these complex datasets poses significant challenges. How can we interpret perturbation effects, establish associations between molecular profiles and study variables, or detect latent variables representing key biological elements like cell types or states? Crucially, how can we achieve these goals with statistical robustness and scientific rigor, facilitating clear and convincing reporting?This course addresses those essential questions, providing participants with foundational mathematical and conceptual understanding of integrative multi-modal data analysis methods. Through hands-on sessions using state-of-the-art datasets, attendees will explore different software tools, assess data quality and results, identify potential pitfalls, evaluate performance, optimize model parameters, interpret outcomes effectively, and embrace open-science practices. Methods covered include factor analysis, multi-table ordination and dimensionality reduction techniques, notably the widely utilised Multi-Omics Factor Analysis (MOFA) and more recent approaches, developed by the course faculty.AudienceThis course is aimed at bioinformatics scientists, PhD students and post-docs aiming to improve their skills in multi-omics data integration methodologies. Scientists who themselves have a training role are particularly encouraged to apply. Experience with R and/or Python and willingness to work with both is a prerequisite for this course.ModulesMulti-table integration: motivation, concepts and theoryMulti-omics case studies, single cell multi-omics, spatial omicsData management and open science related topics in multi-modal data integrationVisualisation and interactive data analysisLearning outcomesThe course will provide researchers with an overview and the theoretical foundations of state-of-the-art methods for multi-modal integration, with a focus on omics data. In practical sessions on relevant real-world examples from single-cell and bulk multi-omics studies, participants will gain familiarity with software implementations and learn about practical aspects, including quality assessment of inputs and outputs, method performance assessment, choice of tuning parameters, interpretation of the model fit and potential pitfalls.What past participants say about the course“The course was a fantastic overview of the state-of-the-art in multi-omics integration with exposure to the top methods and researchers in the field. Getting to discuss open problems with the speakers and other participants was invaluable and I’ve made some great connections with other attendees which I hope to continue to develop.” – Eleanor Williams, Wellcome-MRC Cambridge Stem Cell Institute, UK“The course provides a comprehensive overview of different multiomics data integration techniques with real-life applications and an excellent opportunity to network with fellow participants, speakers, and method developers.” – Adhideb Ghosh, ETH Zurich, Switzerland