• Format: Hybrid

• Date: 7 and 8 July 2025 (two days)

• Location: Montenegro University, Cetinje, Montenegro

• Organization Committee: Milana Grbic, Jeanine Houwing-Duistermaat, Nevena Ilieva-Litova, Vladimir Jacimovic, Andigoni Malousi

• Local Organization Committee: Vladimir Jacimovic,  Anton Gjokaj, Nevena Miailovic, Goran Popivoda (University of Montenegro)

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WG2 of Dynalife is dedicated to advancing statistical and probabilistic modelling, bioinformatics, and machine learning for biological data to underpin the theoretical modelling of WG1. We are pleased to propose a two-day intensive Workshop, in Cetinje, Montenegro, from June 30th to July 1st. Following the success of the previous WP2 Workshop in Nijmegen last September—where participants expressed a strong interest in network-related themes—this workshop will further explore various aspects of biological networks, including their construction, analysis, and applications. Additionally, we will cover cutting-edge methodologies for integrating computational and experimental biological data. While networks and data integration form the core themes, discussions on other topics aligning with WG2’s goals, as well as their intersections with WG1’s objectives, are encouraged.

Networks are a broad area of research in disciplines such as mathematics, statistics, computer science, bioinformatics, and social sciences. They provide valuable insights by summarizing high-dimensional data and visualizing complex relationships. Key topics for discussion in this workshop may include:

 

• Network topology and structure

• Identification of key nodes and elements

• Integration of multi-source data for network construction

• Merging multiple network datasets

• Estimation methods from high-dimensional data

• Interpreting biological network structures

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A significant challenge in modern biology is integrating various types of data, including large synthetic datasets, small datasets from molecular simulations, and sparse, often noisy experimental data. While experimental data may be limited and biased, it can contain valuable new knowledge. This workshop will explore methods for combining these diverse data sources and extracting meaningful predictions regarding molecular interactions from noisy and biased datasets. Relevant methodological techniques include dynamic modelling, digital signal processing, and statistical integration.

The aim of the workshop is to enhance insights through network visualization and improve efficiency through data integration. The event will feature four keynote lectures alongside selected presentations from participants. Ample time will be dedicated to discussions aiming to foster collaborations on these topics. Depending on the number of participants, we may also incorporate poster presentations.

This workshop is designed for computer scientists, statisticians, and bioinformaticians seeking to deepen their expertise and exchange knowledge, as well as theoretical biologists and dynamicists looking to shape new methodologies in these critical areas. Early career researchers are particularly encouraged to participate.

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Grant Period Goals Addressed:
GAPG1 Convergence, integration, and testing of theoretical models including simulations and ML data GAPG 3 Exploration of potential applications GAPG 4 Integration, training, and promotion of specific collaborations in the modelling of genomic information GAPG 6 Promotion of Scientific Excellence and Cross-field Interaction across the Action GAPG 7 Identification of complementary and synergic international partners

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Expected Outputs:

• Knowledge exchange and networking opportunities

• Establishment of new research collaborations

• Abstract book documenting key presentations