CAIMed Meet-up AI Powered Approaches in Infection Research
CAIMed Meet-up: AI Powered Approaches in Infection Research
We are pleased to invite you to the upcoming CAIMed Meet-up on January 30 2025, from 1:00 p.m. to 5:00 p.m. PM at TWINCORE, Zentrum für Experimentelle und Klinische Infektionsforschung GmbH. The meet-up will focus on "AI Powered Approaches in Infection Research",
Agenda
1:00 p.m. – 1:10 p.m. Welcome & Introduction (Prof. Dr. Yang Li, CAIMed, CiiM)
1:10 p.m. – 1:40 p.m. Session 1: AI systems for integrative Multi-Omics Data (Prof. Dr. Tim Beißbarth, University Medical Center Göttingen)
- Exploring how artificial intelligence integrates multi-omics data to uncover complex biological interactions and accelerate insights into infection mechanisms.
1:40 p.m. – 2:10 p.m. Session 2: Defense against respiratory pathogens (Dr.-Ing. Geraldine Nouailles, Charité - Universitätsmedizin Berlin)
- Highlighting the use of AI to enhance understanding of immune responses and develop innovative strategies to combat respiratory infections.
2:10 p.m. – 2:40 p.m. Session 3: Machine learning applications to bacterial genomics, from essential genes to antimicrobial resistance (Prof. Dr. Marco Galardini, Twincore, MHH)
- Demonstrating machine learning's role in identifying essential bacterial genes and uncovering mechanisms behind antimicrobial resistance.
2:40 p.m. – 3:00 p.m. Coffee Break
3:00 p.m. – 4:20 p.m. Session 4: cutting-edge tocology powered by AI in infection research (CAIMed, Junior Research Group on AI & Bioinformatics)
1. From big data to immunological insights, Dr. Saumya Kumar
- Leveraging big data analytics to decode immune system responses and provide a deeper understanding of infection biology.
2. AI and gene regulatory network analysis: a practical introduction, Dr.-Ing. Jalil Nourisa
- Introducing AI-driven approaches for analyzing gene regulatory networks, paving the way for insights into genetic regulation during infections.
3. Spatial transcriptomics reveals abnormal immune and cell-matrix remodeling programs in MTB granuloma formation, Dr. Xun Jiang
- An example to show what Spatial transcriptomics can bring to infection research.
4. AI powered segmentation and deconvolution in Spatial transcriptomics data analysisa, Yuesi Xi, M.Sc.
- Presenting advanced AI tools for segmenting and deconvoluting spatial transcriptomics data to better understand cellular architecture in infected tissues.
4:20 p.m. – 5:00 p.m. Reception & Networking
CAIMed is funded by the Ministry of Science and Culture of Lower Saxony with funds from the program zukunft.niedersachsen of the VolkswagenStiftung
Ticket(s)
CAIMed is the Lower Saxony research center for artificial intelligence and causal methods in medicine. We develop innovative methods for improved, personalized healthcare and contribute to the management of widespread diseases such as cancer, cardiovascular diseases and infections. The combination of excellent locations in Lower Saxony for methodical AI research, data-intensive medicine, medical informatics and basic medical research creates a unique flagship project for research into AI and personalized medicine.
CAIMed relies on the linking of research data, clinical data and patient care data as well as the use of artificial intelligence and causal methods. This enables prevention, diagnostics, therapy and monitoring of therapeutic success to become more effective and efficient and the individual needs of each person to be better identified and served.