Keynote Speakers
Meet our keynote speakers!
Artificial Intelligence Reconstructing biological function with deep learning-based de novo protein design
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Prof. Dr. Lukas Milles
Gene Center, LMU Munich MPI of Biochemistry, Martinsried
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De novo protein design has experienced a machine learning-fueled revolution, vastly expanding our ability to design complex and functional proteins beyond those found in nature. I will discuss recent work at the intersection of de novo protein design, deep learning and fundamental biophysics of protein function regarding both computational design and wet lab biophysical characterization. The work will touch upon control over three levels of protein structure: oligomeric state and symmetry, secondary structure and scaffolding of structural motifs, and finally control over amino acid side chain orientation for catalytic activity.
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Science Communication
"Emil's World - A Society in Transition"
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Prof. Dr. Ranga Yogeshwar
My grandson Emil was born in 2020 and the chances are good that his generation will live up to the next century. In which world will Emil live? His generation is growing up surrounded with talking devices, artificial intelligence, a new medicine, but also networked media and a change in social interactions. During the corona-pandemic we all have experienced disruptive changes within the world of business with more to come as artificial intelligence, still in its infancy, begins to shape our lives. As the impacts of global climate change are becoming more and more visible transformation is a must. But how can we reduce the footprints of our current lifestyles? Besides technological solutions we urgently need a deeper culture-shift. Within the young generation, traditional values are changing towards a growing focus on sustainability and meaningfulness. In a historic global transformation Emil's world will have to leave behind the "business as usual" of past generations heading towards a world with new priorities and values.
Artificial Intelligence Reconstructing biological function with deep learning-based de novo protein design
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Prof. Dr. Lukas Milles
Gene Center, LMU Munich MPI of Biochemistry, Martinsried
​
De novo protein design has experienced a machine learning-fueled revolution, vastly expanding our ability to design complex and functional proteins beyond those found in nature. I will discuss recent work at the intersection of de novo protein design, deep learning and fundamental biophysics of protein function regarding both computational design and wet lab biophysical characterization. The work will touch upon control over three levels of protein structure: oligomeric state and symmetry, secondary structure and scaffolding of structural motifs, and finally control over amino acid side chain orientation for catalytic activity.
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Synthetic Biology
Synthetic Minimal Bacterial Cell: How and why it was made and what has it taught us
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Prof. Dr. John Glass
J. Craig Venter Institute
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The world’s first near minimal bacterial cell, JCVI-syn3.0, was constructed almost a decade ago. The J. Craig Venter Institute (JCVI) built JCVI-syn3.0 to be a chassis for the investigation of the first principles of cellular life. To build this cell, the JCVI had to invent new synthetic biology technologies that transformed the whole bioengineering field and even affect the lives of ordinary humans. Once we built our minimal cell our research focus changed from synthetic biology technology development to basic biology research. My lab has and continues to use our minimal bacterial cell to probe topics such as what are the essential set of tasks that a living cell must perform, how did modern cell division evolve, what is the origin of chromatin, and can we use what we learned in building our cell to construct living synthetic cells from non-living parts.​
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Personalized medicine
Integrative Metabolomics for Precision Medicine in Pregnancy
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Prof. Dr. Liang Liang
Department of Obstetrics & Gynecology, Medical College of Wisconsin
Dr. Liang is passionate about developing diagnostic and therapeutic solutions for pregnancy complications. She has globally characterized thousands of molecular features from blood and urine samples of pregnant women, and established the “metabolic clock” of pregnancy based on blood metabolites using machine learning. She received postdoctoral training at Stanford University, holds degrees from Tsinghua University and the Stowers Institute, and is a graduate of the Ignite program at Stanford University’s Graduate School of Business.
Science and Politics
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Discussion with keynotes lead by Prof. Dr. Peter Becker (LMU)
Translational medicine
Functional Screening in Human Spleen Identifies a Natural Adjuvant Underlying Vaccine Response Variability
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Prof. Dr. Guangbo Chen
Department of Obgyn and Center for Immunology, Medical College of Wisconsin
Dr. Chen recently finished a Life Science Research Foundation Fellowship (Sponsored by Eli Lilly) in Mark Davis's lab at Stanford University. He is now an assistant professor at the Department of Obgyn and Center for Immunology at the Medical College of Wisconsin. Using spleen tissue, a life gift from transplant organ donors, Dr. Chen aims to reconstitute the immune response in vitro and inform the rational design of vaccines and immunotherapy. About the Talk: Functional Screening in Human Spleen Identifies a Natural Adjuvant Underlying Vaccine Response Variability.