English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models

Zi, Z. (2011). SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models. Bioinformatics, 27(7), 1028-1029. doi:10.1093/bioinformatics/btr038.

Item is

Files

show Files
hide Files
:
Zi.pdf (Publisher version), 145KB
Name:
Zi.pdf
Description:
-
OA-Status:
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
© 2011 Oxford University Press
License:
-

Locators

show

Creators

show
hide
 Creators:
Zi, Zhike1, Author           
Affiliations:
1Cell Signaling Dynamics (Zhike Zi), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2117284              

Content

show
hide
Free keywords: -
 Abstract: Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors.

Details

show
hide
Language(s): eng - English
 Dates: 2011-02-082011-04-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1093/bioinformatics/btr038
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Bioinformatics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Oxford : Oxford University Press
Pages: - Volume / Issue: 27 (7) Sequence Number: - Start / End Page: 1028 - 1029 Identifier: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991