This is a website for an H2020 project which concluded in 2019 and established the core elements of EOSC. The project's results now live further in www.eosc-portal.eu and www.egi.eu
This is a website for an H2020 project which concluded in 2019 and established the core elements of EOSC. The project's results now live further in www.eosc-portal.eu and www.egi.eu
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
First two days will cover introductory sessions covering Linux, programming (R/Python) and statistics, in order to make sure all participants are at the same level and have necessary software and packages installed and configured.
Days 3-5 will be filled with workshops and lectures on Machine Learning related topics given by the invited speakers.
Days 6-8 will consists of 6 hackathon projects (~6 participants per each project). Every project will be guided by the mentor.
On the last day we'll conclude all hackathon projects with presentations, discussion and summary.
Białobrzegi, a village in central Poland, in Masovian Voivodeship, about 25 kilometers north of Warsaw.