skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • Home
  • Search Results
  • Page 1 of 1

Search for: All records

Creators/Authors contains: "Noid, W_G"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; ; ; (, Proceedings of the National Academy of Sciences)
    Significance Physical phenomena can often be described by surprisingly few order parameters. Unfortunately, it is challenging to identify these essential degrees of freedom. Here we develop a statistical physics framework for exploring the landscape of order parameters, or coarse-grained representations, for a microscopic protein model. We employ Monte Carlo methods to statistically characterize this landscape. We define metrics assessing the intrinsic quality of each representation for preserving the configurational information and large-scale motions of the underlying microscopic model. Interestingly, these metrics are anticorrelated in low-resolution representations. Moreover, below a critical resolution, a phase transition qualitatively distinguishes superior and inferior representations. Finally, we relate our work to recent approaches for clustering graphs and detecting communities in networks. 
    more » « less