LNA++: Linear Noise Approximation with First and Second Order Sensitivities

Justin Feigelman, Daniel Weindl, Fabian J. Theis, Carsten Marr, Jan Hasenauer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


The linear noise approximation (LNA) provides an approximate description of the statistical moments of stochastic chemical reaction networks (CRNs). LNA is a commonly used modeling paradigm describing the probability distribution of systems of biochemical species in the intracellular environment. Unlike exact formulations, the LNA remains computationally feasible even for CRNs with many reactions. The tractability of the LNA makes it a common choice for inference of unknown chemical reaction parameters. However, this task is impeded by a lack of suitable inference tools for arbitrary CRN models. In particular, no available tool provides temporal cross-correlations, parameter sensitivities and efficient numerical integration. In this manuscript we present LNA++, which allows for fast derivation and simulation of the LNA including the computation of means, covariances, and temporal cross-covariances. For efficient parameter estimation and uncertainty analysis, LNA++ implements first and second order sensitivity equations. Interfaces are provided for easy integration with Matlab and Python. Implementation and availability: LNA++ is implemented as a combination of C/C++, Matlab and Python scripts. Code base and the release used for this publication are available on GitHub (https://github.com/ICB-DCM/LNAplusplus ) and Zenodo (https://doi.org/10.5281/zenodo.1287771 ).

Original languageEnglish
Title of host publicationComputational Methods in Systems Biology - 16th International Conference, CMSB 2018, Proceedings
EditorsDavid Safranek, Milan Ceska
PublisherSpringer Verlag
Number of pages7
ISBN (Print)9783319994284
StatePublished - 2018
Event16th International Conference on Computational Methods in Systems Biology, CMSB 2018 - Brno, Czech Republic
Duration: 12 Sep 201814 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11095 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Computational Methods in Systems Biology, CMSB 2018
Country/TerritoryCzech Republic


  • Automatic construction
  • Linear noise approximation
  • Numerical simulation
  • Python
  • Sensitivity analysis


Dive into the research topics of 'LNA++: Linear Noise Approximation with First and Second Order Sensitivities'. Together they form a unique fingerprint.

Cite this