DA 1.0: Parameter estimation of biological pathways using data assimilation approach

Chuan Hock Koh, Masao Nagasaki, Ayumu Saito, Limsoon Wong, Satoru Miyano

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Summary: Data assimilation (DA) is a computational approach that estimates unknown parameters in a pathway model using time-course information. Particle filtering, the underlying method used, is a well-established statistical method that approximates the joint posterior distributions of parameters by using sequentially generated Monte Carlo samples. In this article, we report the release of Java-based software (DA 1.0) with an intuitive and user-friendly interface to allow users to carry out parameters estimation using DA.

Original languageEnglish
Article numberbtq276
Pages (from-to)1794-1796
Number of pages3
JournalBioinformatics
Volume26
Issue number14
DOIs
Publication statusPublished - 2010 May 26

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint Dive into the research topics of 'DA 1.0: Parameter estimation of biological pathways using data assimilation approach'. Together they form a unique fingerprint.

Cite this