NTB-W03

• Date: Tuesday, September 13th
• Time: 13:30 to 16:30 CEST
• Format: Virtual

• Arnau Montagud, Barcelona Supercomputing Center (BSC), Barcelona (Spain)
• Marta Lloret-Llinares, European Bioinformatics Institute, (EMBL-EBI) (United Kingdom)
• Renata Giménez, Barcelona Supercomputing Center (BSC), Barcelona (Spain) – Helper
• Mariola Tàrrega-Moltó, Barcelona Supercomputing Center (BSC), Barcelona (Spain) – Helper

• Simulations of cells
• Metabolic modelling
• Multiscale modelling
• Signalling networks modelling
• HPC
• Data analysis
• Machine learning

High-Performance Computing (HPC) environments are fundamental infrastructures in current research communities. They are becoming an essential tool in many different fields like climate prediction, engineering simulations or material science, among others, due to their ability to power up data analysis, storage and large-scale processing.

In Computational Biology, HPC has been crucial for storing, processing and analysing the
exponentially growing amount of biomedical data provided by the new sequencing technologies. These resources paved the way for novel modelling tools that yielded results in a wide variety of biomedical applications, including cell fate, chromatin dynamics, genome integrity, molecular pathways and tissue simulations. The use of these tools in combination with clinical data provide a unique and valuable description of aberrant molecular features behind complex diseases, like cancer or infections. In this context, new computational tools have been designed to properly leverage HPC resources and address more realistic scenarios. Scaling up the tools’ scope usually allows for the integration of different data types, but also requires using model parameterization and optimization techniques to deal with the higher number of parameters. HPC benefits such approaches either by
offering the opportunity to use shared memory or parallel processes to address complex problems. Another aspect is the development of workflows and infrastructure to ease the parallelisation of otherwise sequential code and use of tools for model parameterization and exploration.

These ongoing developments will shape future directions, essential to solving challenging paradigms in personalised medicine and drug design or drug repurposing, to name a few.

• Scope: The aim of the workshop is to bring together researchers working in computational systems biology and High-performance computing (HPC) to foster novel developments at the interface of these fields.
• Motivation: Researchers from computational modelling and HPC fields rarely have the opportunity to exchange, discuss and identify limitations, complementarities and common grounds.
• Goals: We aim to bring together researchers that develop or employ methodologies and tools for data analytics, modelling and/or machine learning focusing on simulating cellular behaviours. The focus will be on identifying ways to combine HPC-based methods to scale up computation with mechanistic and statistical modelling to build predictive dynamical models.

Elana J. Fertig
Director of the Research Program in Quantitative Sciences, Co-Director of
the Convergence Institute and Associate Director of Quantitative Sciences at the Johns Hopkins Kimmel Cancer Center.

The target audience encompasses:

• PhDs
• Post-doctorant fellows
• Advanced researchers and participants from private companies from the field of Systems Biology
• Computational Biology
• Computer Science and Bioinformatics who apply or are interested in applying computational modelling techniques for studying cellular functions

TIME	CONTENT
13:30 – 14:15	“Machine learning for spatial multi-omics in cancer” Elana J Fertig
14:15 – 14:30	Scalable Calibration of Large Cancer Related Signaling Pathway Models in HPC Environments Fabian Fröhlich
14:30 – 14:45	EpiLog, a computational tool for logical multicellular models Claudine Chaouiya and Pedro T. Monteiro
14:45 – 15:00	Break
15:00 – 15:15	A global method for simulating intracellular signaling reduces computational time in multiscale agent-based models with systems biology applications Daniel Bergman and Trachette Jackson
15:15 – 15:30	Agent-based model to simulate immune cell response during early bone fracture healing Edoardo Borgiani, Gabriele Nasello and Liesbet Geris
15:30 – 15:45	Interfacing the agent-based modelling software BioDynaMo with Approximate Bayesian Computation to simulate the growth of neuronal morphologies Tobias Duswald, Tom Thorne, Barbara Wohlmuth and Roman Bauer
15:45 – 16:00	An agent-based model of tumor-associated macrophage differentiation in chronic lymphocytic leukemia Nina Verstraete, Malvina Marku, Marcin Domagala, Hélène Arduin, Julie Bordenave, Jean-Jacques Fournié, Loïc Ysebaert, Mary Poupot and Vera Pancaldi
16:00 – 16:15	Multiscale modeling allows to study the different modes of cancer cell invasion Marco Ruscone, Arnau Montagud, Philippe Chavrier, Olivier Destaing, Andrei Zinovyev, Emmanuel Barillot, Vincent Noël and Laurence Calzone
16:15 – 16:30	PhysiBoSS allows for drug synergies studies in real-size tumours simulations Miguel Ponce de Leon, Arnau Montagud, Othmane Hayoun-Mya, Thaleia Ntiniakou, Gaurav Saxena, David Vicente and Alfonso Valencia

We will select most of the speakers from abstracts sent to the NTB-W03 | Simulating
cellular behaviours: advancing HPC-enabled Computational Biology Easychair track before August 21st.

The scientific committee to select abstracts consists of:

• Thaleia Ntiniakou, Barcelona Supercomputing Center (BSC)
• Miroslav Kratochvil, University of Luxembourg
• Laurence Calzone, Institut Curie
• Jesse Harrison, CSC – IT Center for Science
• Pablo Rodríguez Mier, Universitätsklinikum Heidelberg (UKHD)
• Vincent Noel, Institut Curie
• Marco Ruscone, Institut Curie
• Javier Conejero, Barcelona Supercomputing Center (BSC)