Training events

Advances in biological and medical technologies drive continuous generation of large amounts of biomedical Big Data. European Nucleotide Archive stores 260 million sequences comprising 339 trillion nucleotides. This will double in less than 3 years if the current rate of growth is sustained! Given the exponential progress in sequencing technology the increase will only get steeper, entailing an intensified demand for experts in NGS data analysis. Big Data requires applying new solution to leverage its potential. Machine Learning (ML) is the answer to the increased complexity of research problems in science, industry and in everyday life. It is our conviction that knowledge of the ML techniques is a crucial skill every data scientist should acquire throughout their training.

For above reasons, #NGSchool2019: Machine Learning for Biomedicine will be focused on Machine Learning (ML) and its application in Bioinformatics & NGS Data Analysis as well as personalised medicine. We will cover the following subjects:

• Introduction to Linux, programming (R and Python) and statistics

• Tools for efficient and reproducible research

• Modern  and  libraries/packages for biomedical data science

• Deep learning in long read sequencing data analysis

• Statistical and probabilistic analysis of biomedical data

• Integration of genomics data using ML for understanding gene regulation in its three dimensional context

• Quality control and typical mistakes of a beginner ML user

The worshop will introduce HADDOCK, (High Ambiguity Driven protein-protein DOCKing) which is an information-driven flexible docking approach for the modeling of biomolecular complexes, and PMX which is a service for users who need to do free energy calculations. PMX utilizes the Gromacs classical molecular dynamics simulation engine to perform calculations at the background. The workshop also covers advanced usage of Gromacs itself in particular on HPC environment.

From 23-27 September 2019, EUDAT CDI and PRACE are organising a Summer School on "Managing scientific data from analysis to long term archiving". Taking place in the beautiful location of the International Centre for Theoretical Physics (ICTP) of Trieste (Italy), the school aims to build the foundational skills for managing and processing data within complex research environments. Starting from real use cases, the school will focus on all the steps part of a typical research data lifecycle (data discovery; data processing; data analysis; data preservation and publishing) combining frontal lessons with hands-on sessions.

The School is multi-disciplinary and targeted at postgraduate researchers including bachelor degree or equivalent in fields such as physics, statistics, computer science, computer vision, biology, medicine,engineering working at any research institute, with experience in data analysis, in computing or in related fields.

The Third School on Open Science Cloud will be held in Bologna, 16-20 September 2019 and is organised by INFN, University of Perugia and University of Bologna.