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
#NGSchool2019 will be held on 24-31 Oct in Białobrzegi, Poland (see Venue). We'll invite ~60 participants (40 students and 20 speakers). You can find all details about this edition in Book of abstracts. All materials from this edition are available at our github.
This year we'll host introductory sessions, lectures, workshops and hackathons. 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. For more details, check our program.
Similarly to previous years, we'll make sure there is plenty of fun beside hard working during workshops :) You can check photos from previous editions for a sample of that.
- Katarzyna Kędzierska, WCHG, OX, Oxford, GB
- German Demidov, University of Tuebingen, DE
- Samantha Filipów, IITD PAN, Wrocław, PL
- Alina Frolova, IMBG, Kyiv, UA
- Maja Kuzman, University of Zagreb, HR
- Maciej Łapiński, IIMCB, Warsaw, PL
- Leszek Pryszcz, CRG, ES / IIMCB, PL
- Eugeniusz Tralle, IIMCB, Warsaw, PL
Registration was opened from Monday, March 4, 12 PM CET, and closed at 23:59 CET on July 26. You can find more information about the selection procedure.
Thanks to generous support from International Visegrad Fund and other sponsors we are able to set the registration fee at €100! Registration fee covers participation in all course-related activities, as well as, accommodation, meals and coffee breaks during the course. The registration fee can be waived depending on the personal circumstances of the applicant. In addition, a limited number of travel grants are available.
If you are interested in supporting #NGSchool or would like to learn more, don't hesitate to contact us directly. We are looking forward to initiating rewarding and lasting professional relationships.