Difference between revisions of "Home"

From merlin
Jump to: navigation, search
Line 25: Line 25:
==Ongoing work==
==Ongoing work==

Revision as of 15:08, 13 December 2019



merlin version 4 will be released on 5th of November 2019

We are proud to announce that the latest version of merlin will be released on the 5th of November 2019, available for download in this website.

S2M2 - Summer School in Metabolic Modeling (3-7 June 2019)

BioSystems group is organizing a 5-day course on metabolic modelling – Summer School in Metabolic Modeling. The course will cover the full process from model reconstruction to phenotype prediction ns using genome-scale metabolic models. The focus of the course will be on user-friendly tools for metabolic model reconstruction (merlin) and simulation (Optflux) and to introduce experimental procedures to improve those models. See more at http://s2m2.bio.di.uminho.pt/

tutorial available

A tutorial on Reconstructing high-quality large-scale metabolic models with merlin was published in:
Metabolic Network Reconstruction and Modeling: Methods and Protocols, Vol. Methods in Molecular Biology 1716, Springer, 2018. ISBN: 978-1-4939-7528-0, 1-36

merlin is now published

Dias, O., Rocha, M., Ferreira, E.C. and Rocha, I. (2015) Reconstructing genome-scale metabolic models with merlin. Nucleic Acids Res., 10.1093/nar/gkv294.

TRIAGE is also published:

Dias, O., Gomes, D., Vilaca, P., Cardoso, J., Rocha, M., Ferreira, E., & Rocha, I. (2016). Genome-wide Semi-automated Annotation of Transporter Systems. IEEE/ACM Transactions on Computational Biology and Bioinformatics / IEEE, ACM, (1), 1–1. http://doi.org/10.1109/TCBB.2016.2527647


merlin is a simple, graphical and user-oriented solution for the reconstruction of genome-scale metabolic models.

It will guide you along the model reconstruction, providing several tools that help to improve and curate the model throughout the whole process.


Ongoing work

We are currently working on the following features and will release a new version of merlin in the near future:

  • Integration of modelSEED metabolic data.
  • Integration of BIGG metabolic data.
  • Development of a plugin towards the integration of regulatory data.

Getting started