[ONLINE] Short course on HPC-based Computational Bio-Medicine

Date: 14/Feb/2023 Time: 10:00 - 16/Feb/2023 Time: 13:30

Place:
online via Zoom

Target group: INTERMEDIATE For trainees with some theoretical and practical knowledge  

Cost: There is no registration fee. The course is free of charge.  

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Tuesday 14th of February 2023: HPC-basics track & Life sciences [HYBRID: on site and online]
9:30 - 11:00 CET “First steps in the HPC environment”. Part I C. Teijeiro-Barjas and  Xavier Álvarez (SURFsara) & Okba Hamitou (Atos). This training provides information and tutorials about how to access and perform basic actions on a supercomputer. This session covers a wide range of topics: some theoretical aspects such as the description of the processor architecture, the several levels of code parallelization, and practical aspects such as the batch scheduler usage, compilation and optimization guidelines towards good performance achievements.
11:00 – 11:30 CET Coffee Break
11:30 - 14:00 CET “First steps in the HPC environment”. Part II C. Teijeiro-Barjas (SURFsara) & Okba Hamitou (Atos).
14:00 CET Adjourn

Wednesday 15th of February 2023: Molecular medicine track & Life sciences [HYBRID: on site and online]
9:30 - 11:25 CET “Molecular Medicine”. Andrea Townsend-Nicholson (UCL). This workshop in molecular medicine aims to provide participants with a theoretical understanding of the importance of the relationship between human microbiomes – the microorganisms present in and on the human body – and human health and with the practical opportunity to use state of the art computational resources to run a metagenomics pipeline. Using marker gene abundance data and the QIIME2 computational workflow, the identity of the different bacterial taxa present in Next Generation Sequence data obtained from medically-relevant microbiome samples will be obtained and the statistical significance of the experimental hypothesis determined.
11:25 – 12:00 CET Coffee Break
12:00 - 14:00 CET “Introduction to Computer-Aided Drug Design (CADD)”. Alexander Heifetz (Evotec). The subject of my presentation is application computer-aided drug design (CADD) methods in drug design. CADD is the application of computer modelling techniques to drug design process. I will provide a brief overview of these CADD approaches illustrated by the examples taken from real drug discovery campaigns. In my presentation, I will cover the basic theory behind these methods and describe various techniques like virtual screening, homology modeling, docking, structure- and ligand- based drug design, fragment-molecular orbital (FMO) quantum mechanics analysis of protein-water-ligand interactions, GPCR modeling, structure-activity analysis (SAR) and artificial intelligence/deep learning.
14:00 – 15:00 CET Lunch Break
15:00-16:30 CET “The use of multiscale modelling to build a virtual patient from the cell-level up” Arnau Montagud (BSC, PerMedCoE). Multiscale modelling is a versatile methodology that can reconcile cell intracellular events (such as mutation or drug effects) with cell population effects (such as cancer phenotypes or clonal heterogeneity formation). These models are helping researchers address the diseases at the cell level by enabling the study of the consequences of mutations and genomic alterations in specific signalling and metabolic pathways of the different cell types, the modelling of the temporal evolution of the complete tumour and its microenvironment and the prediction of the response to different drugs.In this talk, we will introduce the basics of multiscale modelling (Metzcar et al., 2019), the use of Boolean- logic-based models of signalling pathways (Stoll et al., 2017), and the simulation of tumour evolution with agents representing cell types (Ghaffarizadeh et al., 2018). Specifically, we will present tools to tailor a Boolean model to a given patient’s data (Béal et al., 2019; Montagud, Béal, et al., 2021) and simulate the interplay of genetic and environmental perturbations in the context of cancer cells’ resistance to drugs (Letort et al., 2019; Ponce-de-Leon et al., 2022). Finally, we will present recent advances in using such tools in pre-exascale high-throughput computing clusters to simulate cancer tumours of millions of cells and simulate thousands of patients in optimised analysis pipelines that go from patients’ genomic information to simulation results (Montagud, Ponce-de-Leon, et al., 2021; Saxena et al., 2021).
16:30 CET Adjourn

Thursday 16th of February 2023: Computational Mechanics track
9:30-11:25 CET
“Fluid-Structure Interaction methods for biomechanics”. David Oks(BSC) & Cristobal Samaniego(BSC). During this hands-on course, different approaches for modelling fluid-structure interaction (FSI) couplings will be explored. The working principles of both boundary-conforming and immersed methods will be introduced in order to understand the benefits of using one or another in diverse applications. Relevant aspects of high- performance computing (HPC) will also be discussed during the course. Practical exercises will be carried out using Alya, a multi-physics HPC code developed at BSC designed from scratch to run efficiently on supercomputers. We will be running simulations on Marenostrum 4, BSC's supercomputer, in order to get familiarised with an HPC server environment.
11:25 – 12:00 CET Coffee Break
12:00 - 14:00 CET “Zoom in on blood - Using supercomputers for blood flow simulations”  Konstantinos Asteriou (UvA). 1 mm^3 of human blood, that is less than a single drop, contains about 5 million cells. The interaction and deformation of these cells give rise to the unique properties of blood. Modern biomedical research (e.g. on drug delivery, effect of various diseases such as diabetic cells or sickle cell disease) builds on this information. Unravelling detailed biomechanical and rheological processes in flowing blood requires an accurate modelling of these deformable cells and the surrounding fluid on microscopic level. In this lecture an open-source package (www.hemocell.eu) will be discussed that on one hand allow us to model the behaviour of single cells accurately, and on the other hand can scale up to the level of large flows with millions of cells.

END of COURSE