Teaching Machines To Analyze Simulations
Variational autoencoders are used to compress the complex information from a simulation of amyloid assembly. These 'latent models' are the first step toward automated intelligences interpreting and extracting insight from complex biochemical simulations. Read More...
Better Materials: Peptides or Peptoids?
Peptoids & peptides are two types of biopolymers. Mimicking mussel foot proteins, we compared the properties of peptide and peptoid analogues to assess their abilities as materials. Read More...
Understanding Tau To Understand Alzheimers
Tau peptides are associated with neural plaques that form as part of the clinical pathology of Alzheimer's disease. Detailed simulations let us understand how these peptides form plaques and gather insights into how we can better fight the disease. Read More...
Molecular Dynamics First Principles Simulation of Chemical Systems
Solving the Newtonian equations of motion for biochemical molecules provides atomistic levels of visualizable insight of difficult-to-probe systems.
Peptide Aggregation Investigating the Molecular Origins of Disease
The formation of abnormal plaques from natural cellular proteins is clinically associated with disease. Our methods let us investigate this phenomena in detail.
Analysis of Biomolecules Statistical Mechanics & Machine Learning
With approaches ranging from traditional statistical mechanics to novel machine learning algorithms, we quantitatively characterize the properties of simulated biopolymers.
Documentation Simulation and Computation
Centralized documentation and references critical to work in the Shea group. Includes tutorials and reference guides for molecular dynamics tools and general computational resources available to the Shea group.
