Personalized medical profiling is now supplemented with monitoring the dynamics of multiple molecular and physiological measures of health (generalized omics) towards enabling accurate and timely disease diagnosis and treatment. Such measurements can include clinical tests, blood panels, gene expression, protein levels, metabolite measurements, and digital device data from wearable technologies. We focus on the application of time-resolved monitoring to evaluate and interpret microscopic molecular signatures (omics) and macroscopic physiological measurements and how these change over time. The integration of generalized omics based on detected collective temporal trends provides insights into the physiological state of a person and may be used to detect health events. Our long-term vision is to bring non-invasive individualized medicine to the clinic for all, automate the dynamic monitoring and evaluation of active personnel (astronauts), and improve diagnostics in populations with restricted access to healthcare. To achieve these goals, we have built novel integrative analysis frameworks, and software, for multi-omics dynamic data, and use these in the analysis of biological and health Big Data, and classifying disease dynamics. We are investigating experimentally (with clinical samples) and computationally multi-omics integration for monitoring individuals, with a focus on non-invasive saliva diagnostics. In this talk we will focus on two aspects of our research in precision medicine:

Research presented has been funded at MSU by a Jean P. Schultz Endowed Biomedical Research Fund award, and through federal grants by NHGRI/NIH (R00 HG007065, PI: Mias) and the Translational Institute for Space Health through NASA cooperative agreement NNX16AO69A (Project Number T0412, PI: Mias). The content is solely the responsibility of the authors and does not necessarily represent the official views of the supporting funding agencies.

Professor George Mias is an Associate Professor of Biochemistry and Molecular Biology, and Adjunct Professor of Physics and Astronomy, and of Pediatrics and Human Development at Michigan State University (MSU). He is also Division Chief for Systems Biology at the Institute for Quantitative Health Science and Engineering (IQ Center) at MSU. Professor Mias studied Physics at Yale University, receiving a combined BS/MS (2001), MPhil (2003) and PhD (2007), concentrating on theoretical and quantum statistical physics. He was a Lecturer/Assistant in Instruction at Yale before completing postdoctoral work in human genetics in the Laboratory of Professor Michael Snyder at Stanford University. Professor Mias received a Pathway To Independence Award (K99/R00) from the National Human Genome Research Institute of the National Institutes of Health (NIH), and joined MSU in 2014. He has been leading the Systems Biology Division at the IQ Center since its inauguration in 2016.

Professor Mias leads a diverse interdisciplinary team, focusing on identifying collective temporal trends that reflect a person's physiological state by applying dynamic monitoring to integrate, evaluate and interpret microscopic molecular signatures (omics) and macroscopic physiological measurements. Investigations include systems computational and bioinformatics approaches, and applications to critical phenomena, as well as researching various degenerative diseases, aging, immune responses, cancer, and autism. Professor Mias’ team vision is to bring non-invasive individualized medicine to the clinic for all, automate the dynamic monitoring and evaluation of active personnel (astronauts), and improve diagnostics in populations with restricted access to healthcare.

 

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About the EuroCC-2 project

EuroCC 2 will work to identify and address the skills gaps in the European High Performance Computing (HPC) ecosystem and coordinate cooperation across Europe to ensure a consistent skills base.

The role of EuroCC 2 is to establish and run a network of more than 30 NCCs across the EuroHPC Participating States. The NCCs act as single points of access in each country between stakeholders and national and EuroHPC systems. They operate on a regional and national level to liaise with local communities, in particular SMEs, map HPC competencies and facilitate access to European HPC resources for users from the private and public sector.

EuroCC 2 delivers training, interacts with industry, develops competence mapping and communication materials and activities, and supports the adoption of HPC services in other related fields, such as quantum computing, artificial intelligence (AI), high performance data analytics (HPDA) to expand the HPC user base.

 

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This project has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 101101903. The JU receives support from the European Union’s programme Digital Europe and Germany, Bulgaria, Austria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, Greece, Hungary, Ireland, Italy, Lithuania, Latvia, Poland, Portugal, Romania, Slovenia, Spain, Sweden, France, Netherlands, Belgium, Luxembourg , Slovakia, Norway, Switzerland, Turkey, the Republic of North Macedonia, Iceland, Montenegro and Serbia. 

 

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