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DTSTAMP:20250822T115805Z
LOCATION:Room 6.0D13
DTSTART;TZID=Europe/Stockholm:20250616T112000
DTEND;TZID=Europe/Stockholm:20250616T132000
UID:submissions.pasc-conference.org_PASC25_sess137@linklings.com
SUMMARY:MS1D - Geometries and Topology of Learning for Computational Disco
 very in High Dimensional Biological Systems with Applications to Human Hea
 lth
DESCRIPTION:In recent years there has been substantial interest in using m
 achine learning and AI algorithms for data-driven scientific discovery. Th
 is interest has to a large degree been fueled by significant increases in 
 the power of high-performance computing coupled with growing availability 
 of massive data sets, ranging from weather and climate simulations to biol
 ogical studies of the host response to infectious disease. This computatio
 nal and data driven research has led to a number of significant discoverie
 s related to, e.g., protein-protein interactions, biomarkers of infectious
  disease, molecular neuroscience, immunology, cancer, and structural biolo
 gy. This minisymposium will highlight recent work being done at the interf
 ace of high-performance computing, algorithms, mathematics, and computing 
 for understanding complex systems biological systems. It will feature simu
 lations and AI analyses using high-performance computing resources at Oak 
 Ridge National Labs and the National Center for Atmospheric Research (NCAR
 ). The focus will be on health-related applications, including modeling pa
 thogen emergence in relation to climate change, graph learning and statist
 ical shape analysis for understanding complex biological systems and learn
 ing neural activity patterns from deep geometric and topological networks.
 \n\nLearning and Shape Analysis of Pose Image Manifolds\n\nDespite the hig
 h-dimensionality of images, the sets of images of 3D objects have long bee
 n hypothesized to form low-dimensional manifolds. What is the nature of su
 ch manifolds? How do they differ across objects and object classes? Answer
 ing these questions can provide key insights in explaining and ...\n\n\nAn
 uj Srivastava, Benjamin Beadett, and Shenyuan Liang (Florida State Univers
 ity)\n---------------------\nDeveloping a Data - Driven Farmer Vulnerabili
 ty Index for Farms in Rural Communities with High Performance Computing\n\
 nAfrican Swine Fever (ASF) is a highly contagious and deadly viral disease
  infecting domestic and feral swine populations in Africa and Asia and mor
 e recently in the Europe, South America, and Caribbean. ASF has devastatin
 g impacts on swine industries in the affected countries. This study propos
 es to...\n\n\nDavid Kott and Connor Price (Colorado State University), Tom
  Hopson and Jason C. Knievel (NSF - National Center of Atmospheric Researc
 h), Tracy L. Webb (Colorado State University), Olga Wilhelmi (NSF - Nation
 al Center of Atmospheric Research), and Michael Kirby (Colorado State Univ
 ersity)\n---------------------\nComputational modeling of protein structur
 es: Quantifying the effect of mutations on protein structures\n\nPoint mut
 ations in the protein sequences are known to have potential to alter the p
 rotein’s native fold, stability, and functions, and may result in observab
 le disease phenotypes. Currently, there are over 200,000 experimental prot
 ein structures deposited in the Protein Data Bank, enabling the...\n\n\nZh
 uoyi Liu, Alex Calabrese, and Corey O'Hern (Yale University)\n------------
 ---------\nAI-Driven Systems Biology for Addiction: Large-Scale Multi-Omic
 s Network Modeling and AI Agents for Mechanistic Discovery\n\nUnderstandin
 g the genetic and molecular underpinnings of addiction and related disorde
 rs requires integrative approaches that leverage large-scale omics data, n
 etwork biology, and artificial intelligence. This work presents a systems 
 biology framework that combines predictive expression networks, fo...\n\n\
 nDaniel Jacobson and Matthew Lane (Oak Ridge National Laboratory)\n\nDomai
 n: Chemistry and Materials, Climate, Weather, and Earth Sciences, Life Sci
 ences, Physics, Computational Methods and Applied Mathematics\n\nSession C
 hair: Michael Kirby (Colorado State University)
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