BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260807T155808Z UID:61b2906e-2207-4f7e-8650-bebe29d06402 DTSTART:20250912T090000Z DTEND:20250912T170000Z DESCRIPTION:## Overview\nIn recent years\, there has been increasing concer n about the risks associated with data usage\, particularly regarding data sharing. This has led to the introduction of regulations which impose str icter rules on data management. These regulations significantly impact sci entific research\, especially in the biomedical field\, where the sensitiv ity of the data makes multi-center studies more challenging to conduct. \n \nTo address these challenges\, federated learning (FL) has gained popular ity. FL allows multiple parties to collaboratively train a shared machine learning model using their individual data sources without sharing the dat a itself\, thereby enhancing privacy and security. This is typically reali zed with the help of a server that receives non-sensitive information from data-holder parties (e.g.\, parameters from a locally trained model) and aggregates it into a global model. \n\nThis course will give an overview of FL concepts\, including the operational framework\, privacy benefits\, and challenges. It will show how FL can be used in bioinformatics\, coveri ng both federated versions of established bioinformatics algorithms and fe derated machine learning algorithms designed for bioinformatics data. In h ands-on group exercises\, a FL consortium will be simulated using the open -source FL platform FeatureCloud and a basic FL algorithm will be develope d. \n\n## Audience\nThis course is addressed to life scientists and bioi nformaticians\, from academia or industry\, with an interest in machine le arning for bioinformatics applications. \n\n## Learning outcomes\nAt the e nd of the course\, the participants are expected to:\n\n- Develop an under standing of FL concepts\, including its operational framework\, privacy be nefits\, and challenges.\n\n- Gain an overview of federated methods in bio informatics\, including federated equivalents of established bioinformatic s algorithms as well as federated machine learning algorithms applied to b ioinformatics data.\n\n- Acquire hands-on experience using federated learn ing platforms\, such as FeatureCloud.\n\n- Understand the process of devel oping a federated learning algorithm through hands-on experience in a dida ctic exercise.\n\n## Prerequisites\n##### Knowledge / competencies\nPartic ipants should have a basic knowledge of statistics\, machine learning\, an d Python. No previous knowledge on FL is required. \n \n\nThe competences and knowledge levels required correspond to those taught in courses such a s: [First Steps with Python in Life Sciences](https://www.sib.swiss/traini ng/course/20240304_FSWP)\, [Introduction to Machine Learning with Python]( https://www.sib.swiss/training/course/20240527_INMLP)\, and [Introduction to statistics with R](https://www.sib.swiss/training/website/course/202302 06_STATR). Test your skills with Python and statistics with the quiz [here ](https://forms.gle/ZpQFyHHwoPQKJSwv7)\, before registering. \n##### Techn ical\nYou are required to bring your own laptop. Before the course begins\ , participants will receive a guide detailing the necessary software for t he practical activities (Python\, Docker\, featurecloud pip package) and i nstallation instructions. \n\n## Schedule \nThe course is organized into 4 sessions: \n\n* Theory block 1: Introduction to FL \n* Practical block 1: Group exercise simulating a FL consortium with a ready to use algorithm \ n* Theory block 2: FL for Bioinformatics \n* Practical block 2: Group exer cise developing a basic FL algorithm \n\n## Application\nThe registration fees for academics are **100 CHF** and **500 CHF** for for-profit companie s.\n\nYou will be informed by email of your registration confirmation. Upo n reception of the confirmation email\, participants will be asked to conf irm attendance by paying the fees within 5 days.\n\nApplications close on **22/08/2025** or as soon as the places will be filled out. Deadline for f ree-of-charge cancellation is set to **29/08/2025**. Cancellation after th is date will not be reimbursed. Please note that participation in SIB cour ses is subject to our [general conditions](https://www.sib.swiss/training/ terms-and-conditions).\n\n## Venue and Time\nThis course will take place i n East Campus USI-SUPSI\, Lugano-Viganello.\n\nThe course will start at 9: 00 and end around 17:00. \n\nPrecise information will be provided to the p articipants in due time.\n\n\n## Additional information\nCoordination: Pat ricia Palagi\, SIB Training Group\n\nWe will recommend 0.25 ECTS credits f or this course (given a passed exam at the end of the course).\n\nYou are welcome to register to the SIB courses mailing list to be informed of all future courses and workshops\, as well as all important deadlines using th e form [here](https://lists.sib.swiss/postorius/lists/courses.lists.sib.sw iss/).\n\nPlease note that participation in SIB courses is subject to our [general conditions](https://www.sib.swiss/training/terms-and-conditions). \n\nSIB abides by the [ELIXIR Code of Conduct](https://elixir-europe.org/e vents/code-of-conduct). Participants of SIB courses are also required to a bide by the same code.\n\nFor more information\, please contact [training@ sib.swiss](mailto://training@sib.swiss). SUMMARY:Federated Learning in Bioinformatics URL;VALUE=URI:https://www.sib.swiss/training/course/20250912_FEDBX END:VEVENT END:VCALENDAR