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

Editors contains: "Caltais, Georgiana"

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. ; ; (, Lecture notes in computer science)
    Caltais, Georgiana; Schilling, Christian (Ed.)
    Rare events are known to potentially cause pathological behavior in biochemical reaction systems. It is important to understand the cause. However, rare events are challenging to analyze due to their extremely low observability. This paper presents a fully automated approach that rapidly generates a large number of execution traces guaranteed to reach user-specified rare-event states for Chemical Reaction Network (CRN) models. It is enabled by a unique combination of a multi-layered and service-oriented CRN formal modeling approach, a dependency graph method to aid the shortest rare-event trace generation, and randomized compositional testing. The resulting prototype tool shows marked improvement over stochastic simulation and probabilistic model checking and it offers insights into a CRN. 
    more » « less
    Full Text Available