Workshop Data Science, Artificial Intelligence and Impactful Design in Microbiome Medicine
Sano Hosts "Data Science, Artificial Intelligence and Impactful Design in Microbiome Medicine" Workshop
On January 18th and 19th, Sano – Centre for Computational Medicine held a workshop titled “Data Science, Artificial Intelligence, Impactful Design in Microbiome Medicine.” The workshop aimed to enhance participants’ understanding of the technical aspects of data analysis, data visualization, and the available platforms and resources for microbiome data.
Exploring Microbiome Data Analysis
The workshop offered an in-depth introduction to microbiome topics, ranging from an overview of microbiomes to complex sequencing techniques such as the 16S rRNA marker gene sequencing and shotgun metagenomic sequencing. The practical aspects of designing experiments were highlighted, providing attendees with the necessary tools and knowledge to effectively analyze microbiome data. The sessions were particularly beneficial for those new to the field, including healthcare professionals, biologists, and laboratory technicians working with multi-omic data.
Technical Tools and Resources
Participants engaged with popular bioinformatics tools such as QIIME 2 and Qiita, exploring fundamental concepts including metadata, feature table construction, phylogenetic trees, and measures of alpha and beta diversity. These tools were presented not as advanced computational solutions but as practical applications necessary for basic data handling and experiment design in microbiome studies.
Artificial Intelligence and Machine Learning
The sessions also explored the realms of machine learning and deep learning, with a special focus on explainable AI (XAI). This segment of the workshop educated participants on how AI technologies can be leveraged to interpret complex biological data, enhancing their understanding and application in real-world scenarios.
Impactful Design Session
A key component of the workshop was the “Impactful Design” session, where participants had the opportunity to apply their newly acquired skills. They presented their project ideas, which integrated the theoretical knowledge gained with practical applications. This session was crucial for bridging the gap between theory and practice and promoting innovation in health technology.
After “Data Science, Artificial Intelligence and Impactful Design in Microbiome Medicine” Workshop
The “Data Science, Artificial Intelligence, Impactful Design in Microbiome Medicine” workshop at Sano was a step towards combining theoretical knowledge with practical application, fostering interdisciplinary collaboration and innovation in the field of health technology. Participants left with a broader perspective on the technical aspects of microbiome data analysis and practical experiment design, equipped to tackle the challenges in the rapidly evolving domain of biological data analysis
