Event List

EMODnet Chemistry 6 Training Course 2026 | (smr H729)

Audience: researchers data_scientists

Topics: data_science geospatial chemistry environmental_science

Most systems of scientific interest are interacting many-body systems. One typically describes their kinetics in terms of a low-dimensional reaction coordinate, which in general is influenced by the entire system. The dynamics of such a reaction coordinate is governed by the generalized Langevin equation (GLE), an integro-differential stochastic equation, and involves a memory function [1]. I discuss a few examples where the GLE can be used to interpret and model data in different fields of science. Protein-folding kinetics is often described as Markovian (i.e., memoryless) diffusion in a one-dimensional free energy landscape. By analysis of large-scale molecular-dynamics simulation trajectories of fast-folding proteins from the Shaw group using the special-purpose computer ANTON, I demonstrate that the friction characterizing protein folding exhibits significant memory with a decay time that is of the same order as the folding and unfolding times [2]. Memory friction effects lead to anomalous and drastically modified protein kinetics [3]. For the set of proteins for which simulations are available, it is shown that the folding and unfolding times are not dominated by the free-energy barrier but rather by the non-Markovian friction. Memory effects are also present for non-equilibrium systems. Using an appropriate non-equilibrium formulation of the GLE, it is demonstrated that the motion of living organisms is characterized by memory friction, which allows to characterize internal feedback loops of such organisms and to classify and sort individual organisms [3]. The GLE can be even used to predict complex phenomena such as weather data

Audience: researchers faculty postgraduates

Topics: data_science biomedical_engineering physics molecular_biology meteorology

This practical course provides insight into techniques for transcriptome and proteome analysis, offering hands-on experience turning primary data into information for biological interpretation. Participants will learn about gene expression analysis, protein identification and quantification, and use software tools like SearchGUI, PeptideShaker, MaxQuant, and Cytoscape for data integration.

Audience: researchers postdoctoral_researchers postgraduates

Topics: bioinformatics data_science genomics molecular_biology

This course covers the use of computational tools to extract biological insight from omics datasets. The content will explore a range of approaches – from network inference and data integration to machine learning and logic modelling – that can be used to extract biological insights from varied data types. Together these techniques will provide participants with a useful toolkit for designing new strategies to extract relevant information and understanding from large-scale biological data.

Audience: researchers postdoctoral_researchers postgraduates

Topics: bioinformatics data_science machine_learning genomics molecular_biology

The next Global Data Festival will take place in Nairobi, Kenya, from 2 to 5 June 2026. Organized by Global Partnership for Sustainable Development Data (GPSDD) and co-hosted with the Government of Kenya.

Audience: researchers

Topics: data_science artificial_intelligence

The annual international conference on Intelligent Systems for Molecular Biology (ISMB) is the flagship meeting of the International Society for Computational Biology (ISCB). The 2026 meeting is the 34th ISMB conference, which has grown to become the world's largest bioinformatics and computational biology conference. ISMB 2026 will be the year's most important computational biology event! The principal focus of the ISMB conference is on the development and application of advanced computational methods to address biological problems, and it brings together researchers from computer science, bioinformatics, computational biology, molecular biology, mathematics, statistics, and related fields.

Audience: researchers faculty postdoctoral_researchers students postgraduates data_scientists software_practitioners industry

Topics: artificial_intelligence bioinformatics data_science machine_learning genomics molecular_biology

The 25th International Conference on Bioinformatics (InCoB/ISCB-APAC 2026) marks a defining moment in the evolution of bioinformatics in the Asia Pacific region. As the Silver Jubilee edition of the International Conference on Bioinformatics (InCoB), this meeting celebrates 25 years of sustained scientific contribution, regional leadership, and community building under the auspices of Asia-Pacific Bioinformatics Network (APBioNET). At the same time, it inaugurates a long-term strategic collaboration with the International Society for Computational Biology (ISCB) under the ISCB-APAC framework, strengthening the conference’s global engagement while preserving its regional identity. Under the theme “Where Bioinformatics Meets AI – Unlocking the Next Era of Discovery” the conference will explore the transformative convergence of bioinformatics and artificial intelligence in advancing life science research. From foundational methodologies to emerging AI-driven approaches, InCoB/ISCB-APAC 2026 will provide a platform to examine how computational innovation is reshaping biological discovery, precision medicine, systems biology, and translational research. The scientific programme will feature keynote lectures, presentations of original research, plenary discussions, poster sessions, workshops, software demonstrations, and panel dialogues. The meeting aims to bring together researchers, practitioners, educators, and students from across the Asia Pacific region and beyond to exchange ideas, foster collaborations, and collectively shape the next chapter of discovery in bioinformatics.

Audience: researchers students postgraduates clinicians educators industry practitioners

Topics: artificial_intelligence bioinformatics data_science machine_learning genomics

Conference on advanced quantitative methods and analytics for public policy support

Audience: policy_makers researchers

Topics: data_science policy statistics

This course provides an introduction to causal inference and causal representation learning, offering both theoretical foundations and hands-on training. You will learn how to apply these methodologies to various biomedical data types, including clinical, genotype-phenotype, molecular, and multimodal data.

Audience: researchers postdoctoral_researchers students postgraduates early_career clinicians data_scientists practitioners

Topics: bioinformatics data_science machine_learning biomedical_engineering statistics biotechnology genomics molecular_biology clinical_research public_health

Annual conference for representatives of imaging communities and imaging scientists from around the globe. This event is designed for imaging scientists, core facility managers, technology developers, and industry partners to exchange knowledge, explore emerging trends, and discuss what open access in imaging means globally. Through interactive presentations, hands-on workshops, and regional networking sessions, participants will explore the evolution of open access in imaging worldwide.

Audience: researchers faculty postdoctoral_researchers postgraduates policy_makers funders science_communicators industry

Topics: bioinformatics data_science visualization biomedical_engineering biotechnology