MLB2017

Machine Learning for Biologists

In collaboration with

Venue: Fondazione Edmund Mach, San Michele all'Adige, Trento, IT

Date: 04-07/09/2017

Instructors and helpers

• Giuseppe Jurman - Fondazione Bruno Kessler, Trento, IT
• Marco Chierici - Fondazione Bruno Kessler, Trento, IT
• Davide Albanese - Fondazione E. Mach, Trento, IT
• Pietro Franceschi - Fondazione E. Mach, Trento, IT
• Marco Moretto - Fondazione E. Mach, Trento, IT
• Paolo Sonego - Fondazione E. Mach, Trento, IT
• Samantha Riccadonna - Fondazione E. Mach, Trento, IT
• Andrea Cattani - Fondazione E. Mach, Trento, IT

Organisers

• Alessandro Cestaro (Local Organizer, Fondazione E. Mach, Trento, IT )
• Vincenza Colonna (ELIXIR-IIB Training Coordinator Deputy, CNR, IT)

Course Material

Days	Lessons	Tutorials
day 1	Introduction to "omics" data. Principles of data exploration and analysis	Practicals on principles of data exploration and analysis
day 2	Univariate and Multivariate analysis	A gentle introduction to Machine Learning
day 3	Gene Expression Analysis, Data Analysis Plan	DAP practicals

Programme

Monday 04 September 2017 - Introduction
14:00-15:30	Course opening	Participants’ self-presentations
15:30-16:15	Plenary lecture	P. Franceschi, S. Riccadonna	Introduction to "omics" data. Principles of data exploration and analysis
16:15-16:45	Coffee break
16.45-19:00	Practical	P. Franceschi, S. Riccadonna	Practicals on principles of data exploration and analysis
19:30-21:00	Welcome aperitivo at Cantina storica Istituto Agrario San Michele
Tuesday 05 September 2017 - Machine Learning
09:30-09:40	Previously On	Recap of previous lessons by participants
09:40-10:30	Lecture	D. Albanese, P. Franceschi, S. Riccadonna	Univariate and Multivariate analysis
10:30-11:00	Coffee break
11:00-13:00	Practical	D. Albanese, P. Franceschi, S. Riccadonna	Univariate and Multivariate analysis. Practical session with R
13:00-14:30	Lunch
14:30-16:15	Lecture	D. Albanese, P. Franceschi, S. Ricadonna	Machine Learning: introduction and applications to biological data. Classification basics, model selection and prediction
16:15-16:45	Coffee Break
16:45-18:30	Practical	D. Albanese, P. Franceschi, S. Riccadonna	Performance measures and diagnostic plots
Wednesday 06 September 2017
09:30-09:40	Previously On	Recap of previous lessons by participants
09:40-10:30	Lecture	P. Sonego, S. Riccadonna	Analyzing Gene Expression Data
10:30-11:00	Coffee break
11:00-13:00	Practical	P. Sonego, S. Riccadonna	Analyzing Gene Expression Data
13:00-14:30	Lunch
14:30-16:15	Lecture	M. Chierici, G. Jurman	The Data Analysis Plan (DAP) - intro to unbiased pipelines for (binary) classification
16:15-16:45	Coffee Break
16:45-18:30	Practical	M. Chierici, G. Jurman	Implementation of a basic DAP in Python (Scikit-Learn) with feature ranking and classification
19:30-22:00	Social Dinner at Albergo Ai Spiazzi
Thursday 07 September 2017
09:15-09:25	Previously On	Recap of previous lessons by participants
09:25-10:00	Lecture	M. Moretto, A. Cestaro	Gene prediction methods as an example of ML on genomic data
10:00-10:30	Coffee Break
10:30-12:30	Practical	M. Moretto, A. Cestaro	Training a gene prediciton method
12:30-13:00	Wrap-up and feedback

Computing facility instruction

Practical information