International grants

Weave 2023/05/Y/NZ2/00080  

Title: Evolutionary-scale interpretation of protein functions in the human gut microbiome. 

The Weave project aims to create a detailed atlas of human gut protein structures with functional annotations, centered around a Protein Universe Map for navigating the gut microbiome. Leveraging deep learning and evolutionary modeling, it focuses on the 40% of gut proteins with unknown functions. By using advanced tools like AlphaFold2 and deepFRI, overcomes the limitations of traditional annotation methods and paves the way for deeper insights into gut microbiota metabolism and future therapeutic discovery. 

Project Goals: 

  • Catalogue Construction: Assemble a detailed library of gut protein structures and their predicted functions, including modeling novel 3D structures. 
  • Diversity Exploration: Analyze the sequence and structural diversity of functionally unknown proteins within the global protein space. 
  • Evolutionary Tracing: Investigate evolutionary origins and potential relationships of gut proteins across different ecosystems. 
  • Function Prediction: Combine structural data with genomic context to infer biological functions of dark proteins. 

Duration: 19 January 2024 – 18 January 2028 

Project lead: Tomasz Kościółek (Research Team Leader of Structural and Functional Genomics Group) 

Partners/ List of collaborators: 

University of Basel

InSilicoHealth

InSilicoHealth is a European doctoral training programme that combines virtual human twin research, interdisciplinary education, and industry collaboration to address healthy aging—while critically exploring the ethical and societal dimensions of digital health innovation.

Duration:  1 January 2025 – 31 December 2029

Project lead: Maciej Malawski (Extreme-scale Data and Computing)

Coordinated by:

KATHOLIEKE UNIVERSITEIT LEUVEN

Projekt GEMINI Sano

GEMINI

GEMINI is a project which promises to save lives and enhance the well-being of stroke patients, as it aims at improving diagnosis and treatment for acute ischaemic and haemorrhagic stroke.
This aim will be achieved by developing patient-specific decision-making tools and well-established models that can accurately assist in the diagnosis and stratification of stroke patients for tailored treatments.
Multi-organ and multi-scale Digital Twins models will be developed to improve our understanding of and support personalised treatment selection for this severe condition.

Work package:

Sano is responsible for quality assurance (QA) and ensuring proper verification and validation of software that encapsulates computational models of various types of strokes. For Sano, it is a third EC-funded project, along with the ongoing In Silico World and NearData projects. 

GEMINI project website: dth-gemini.eu

Duration: 01.12.2023 – 30.11.2029 

Project lead: Marian Bubak (Scientific Affairs Director)

Partners/ List of collaborators:

  • National Taiwan University (TW)
  • Academisch Medisch Centrum Bij de Universiteit van Amsterdam (AMC) – Coordinator (NL)
  • AMC Medical Research BV (NL)
  • University of Amsterdam (NL)
  • Erasmus Universitair Medisch Center Rotterdam (NL)
  • Politecnico di Milano (IT)
  • Neuravi Limited (IE)
  • National University of Ireland Galway (IE)
  • Universidad Pompeu Fabra (ES)
  • Budapesti Műszaki és Gazdaságtudományi Egyetem (HU)
  • Ansys France SAS (FR)
  • Sano Centrum Zindywidualizowanej Medycyny Obliczeniowej – Międzynarodowa Fundacja Badawcza (PL)
  • Rheinische Friedrich-Wilhelms-Universität Bonn (DE)
  • Insteps BV (NL)
  • Nico-Lab BV (NL)
  • Sim&Cure (FR)
  • Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie (PL)
  • Les Hôpitaux Universitaires de Genève (CH)
  • Zürcher Hochschule für Angewandte Wissenschaften (CH)

NEARDATA 

The goal of  NEARDATA  is to create an extreme data infrastructure mediating data flows between Object Storage and Data Analytics platforms across the Compute Continuum. Novel XtremeDataHub platform is an intermediary data service that intercepts and optimises data flows (S3 API, stream APIs) with high performance near-data connectors (Cloud/Edge). 

  

Sano Team is responsible for:

  • Developing a pipeline for building transcriptomics atlas of selected tissues/diseases, with the use of HPC and Cloud technologies;
  • Federated Learning framework – a set of tools for running Federated Learning experiments on large scale genomics data.

NEARDATA  project website:  https://neardata.eu/ 

Duration: 01 January 2023 – 31 December 2025 

Project lead: Maciej Malawski (Extreme-scale Data and Computing)

Partners/ List of collaborators:

  • UK Health Security Agency (UK)
  • Universitat Rovira i Virgili (ES) – Coordinator
  • Barcelona Supercomputing Center (ES)
  • Technische Universität Dresden (DE)
  • Deutsches Krebsforschungszentrum Heidelberg (DE)
  • European Molecular Biology Laboratory (DE)
  • EMC Information Systems International Unlimited Company (IE)
  • KIO Networks España SA (ES)
  • Sano – Centre for Computational Medicine (PL)
  • Scontain GMBH (DE)

ISW (In Silico World) 

The In Silico World project aims at accelerating the uptake of modelling and simulation technologies used for the development and regulatory assessment of medicines and medical devices, by lowering seven identified barriers: development, validation, accreditation, optimisation, exploitation, information, and training. 

This initiative employs computer models that leverage experimental data for hypothesis testing and outcome prediction. 

Work package:

Scalability and efficient computing (WP5 led by Sano)

This package focuses on creating a sophisticated, user-friendly simulation platform that ensures the repeatability, replicability, and reproducibility of simulation outcomes. It also aims to facilitate efficient access and utilization of computational and storage capacities, both locally and within major European e-infrastructures like PRACE, EOSC, Eudat, and upcoming EuroHPC initiatives. 

ISW (In Silico World)  project website:  https://insilico.world/ 

Duration: 1 January 2021 –31 December 2024 

Project lead: Marian Bubak (Scientific Affairs Director)

Partners/ List of collaborators:

  • Alma Mater Studiorum – Università di Bologna (IT) – Coordinator
  • Universiteit van Amsterdam (NL)
  • Technische Universiteit Eindhoven (NL)
  • Università degli Studi di Catania (IT)
  • Virtual Physiological Human Institute for Integrative
  • Biomedical Research VZW
  • Katholieke Universiteit Leuven (BE)
  • Insilicotrials Technologies SRL
  • Universite de Liege (BE)
  • Erasmus Universitair Medisch Centrum Rotterdam (NL)
  • Budapesti Muszaki es Gazdasagtudomanyi Egyetem (HU)
  • Din Deutsches Institut Fuer Normung E.V. (DE)
  • Mimesis SRL
  • Rsscan International NV (BE)
  • Sano – Centre for Computational Medicine (PL)

Teaming for Excellence  

The goal of the Teaming for Excellence initiative is to establish a world-class research and innovation hub in Kraków, Poland. The Centre will focus its activities on computational diagnostics, a field at the forefront of technological transformation in healthcare. By leveraging advanced statistical models, machine learning, and large-scale data analysis, it will play a pivotal role in the prevention, diagnosis, and treatment of complex diseases.

The Centre aims to streamline healthcare systems, reduce treatment costs, and improve patient outcomes across Europe. As a catalyst for change, it seeks to reshape the future of medicine through computational innovation.

Strategic Objectives: 

  • Conduct advanced research and development in personalised diagnostics and treatment.
  • Support the healthcare industry through modern, high-impact technological solutions.
  • Accelerate the transfer of knowledge and technology within the healthcare sector.
  • Attract investment, foster start-ups, and promote international collaboration.

Teaming project website: https://cordis.europa.eu/project/id/857533 

Duration: 1 August 2019 – 31 July 2026 

Project lead: Maciej Malawski (Research Team Leader of Extreme-scale Data and Computing) 

H2020-EU.4.a. – Teaming of excellent research institutions and low performing RDI regions 

Partners/ List of collaborators:  

  • Centre for New Methods in Computational Diagnostics and Personalised Therapy – Centre (PL) – Coordinator  
  • Narodowe Centrum Badań i Rozwoju  NCBR  (PL)  
  • Forschungszentrum Jülich GmbH  – FZJ  (DE)
  • Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie (PL) 
  • Akademickie Centrum Komputerowe Cyfronet – Cyfronet  (PL)  
  • Fundacja Klaster LifeScience Kraków – KLSK (PL)
  • Fraunhofer–Gesellschaft zur Förderung der angewandten Forschung e.V – Fraunhofer (DE)
  • The University of Sheffield  – USFD (UK)