Please circulate this email to those who might be interested.
ELIXIR-IIB, in collaboration with Fondazione Bruno Kessler and Fondazione E. Mach, Trento, Italy, is pleased to announce the upcoming training course on “Machine Learning for Biologists”.
Deadline for applications: 21 July 2017
Course date: 4-7 September 2017
Selected participants will be notified by 25 July 2017.
A maximum of 24 candidates will be accepted in the course. Priority will be given to candidates from ELIXIR-IIB member institutions and ELIXIR nodes.
VENUE: Fondazione Edmund Mach, Palazzo della Ricerca e della Conoscenza, Via E. Mach 1, San Michele all’Adige (TN), Italy, (zip code 38010).
Full details at: https://elixir-iib-training.github.io/website/2017/09/04/MachineLearning-Trento.html
The aim of the course is to provide a practical introduction to the analysis of “omics” data. Topics will range from data visualization/exploration to univariate/multivariate analysis and machine learning. Practical exemples and applications will be illustrated by using R and Python.
- Data exploration and visualization
- Univariate/Multivariate analysis
- Introduction to machine learning: classifiers, performance measures, diagnostics
- Machine learning tools for the analysis of Gene Expression data
- The Data Analysis Plan (DAP) - intro to unbiased pipelines for (binary) classification
- Performance measures and diagnostic plots - Accuracy, MCC, Stability: theory and graphics
- Differential network analysis – co-expression networks, graph comparison, community detection: theory and examples in R/Python, visualization by the igraph library and use of the ReNette web interface
- Basic application of ML to gene prediction
Should you have any question, do not hesitate to contact the ELIXIR-IIB Training Team (email@example.com) and/or the local organiser Dr. Alessandro Cestaro (firstname.lastname@example.org).
Thank you for your interest,
The Organisers and the ELIXIR-IIB Training Team
Alessandro Cestaro (Fondazione E. Mach, Trento, Italy)
Vincenza Colonna (ELIXIR-IIB Training Team)