Date/Time
Date(s) - 28/09/2023
5:30 pm - 7:00 pm
Location
BT2 Détente / Kitchenette 1st Floor room 101
Categories
Do you like scientific discussion? And how about Pizza?
If we gained your attention with ‘scientific’, or at least with ‘Pizza’, then you are already looking forward to the right event!
Pizza Club is a regularly held Journal Club event co-organized by The Representatives of the Doctoral Programme in Systems and Molecular Biomedicine, part of the Doctoral School in Science and Engineering (DSSE); and the Uni.lu student association ISCB RSG Luxembourg.
In short, Students (PhD candidates) present a scientific paper (+- 20 mins) they find interesting or that inspired the development of their individual PhD project (doesn’t need to be authored by the speaker).
There will be a open discussion round after each scientific presentation (2-3 students per event), followed by informal and fun chatting with some pizzas around!
Júlia ORTÍS SUNYER (link: https://www.linkedin.com/in/ortis-julia/)
Presenter introduction: Júlia is a 1st year PhD student at the Systems Ecology group, part of the LCSB. Her research focuses on the impact of exposures from the gut-microbiome-derived molecular complex in human health and disease.
Article: “HyperVR: a hybrid deep ensemble learning approach for simultaneously predicting virulence factors and antibiotic resistance genes” (link: https://doi.org/10.1093/nargab/lqad012)
Article description: The paper presents HyperVR, a new tool that combines classical machine learning and deep learning to simultaneously and accurately predict virulence factors, antibiotic resistance genes and negative genes by considering both best hit scores and statistical gene sequence patterns.
Jeff DIDIER (link: https://www.linkedin.com/in/jeff-didier-3ab956168/)
Presenter introduction: Jeff is at the beginning of his 3rd year of PhD in biology within the Systems Biology Group of the Department of Life Sciences and Medicine. His main project revolves around biomarker detection in clinical cohort data using machine learning, with current applications on biomedical data in geriatric syndromes (frailty), neurodegenerative diseases (PD), and at the -omics level in subtyping triple negative breast cancer.
Article: “Frailty Level Classification of the Community Elderly Using Microsoft Kinect-Based Skeleton Pose: A Machine Learning Approach.” (link: https://doi.org/10.3390/s21124017)
Article description: The objective of this study was to predict the elderly frailty level utilizing the machine learning approach on skeleton data acquired from a Kinect sensor as developing a real-time classification model of elderly frailty level could be beneficial for designing a clinical predictive assessment tool.
Moreover, each presentation of peer-reviewed papers will be rewarded by 0.5 ECTS!
If we attracted your interest by now, feel free to join the monthly Pizza Club, either as part of Audience or as a registered Speaker. For the latter, please kindly use this form to sign up as an upcoming Speaker, by choosing your category of paper and desired month to present. Looking forward to seeing you at the next Pizza Club!
