Document details

Towards a multivariate analysis of genome-scale metabolic models derived from the BiGG models database

Author(s): Oliveira, Alexandre Rafael Machado ; Cunha, Emanuel Rodrigues ; Cruz, Fernando João Pereira da ; Ribeiro, João Manuel Capela Araújo ; Costa, João Carlos Sequeira ; Sampaio, Marta Sofia Costa ; Dias, Oscar

Date: 2022

Persistent ID: https://hdl.handle.net/1822/74708

Origin: RepositóriUM - Universidade do Minho

Subject(s): Genome-scale metabolic models; Merlin BiGG integration tool; BiGG models; Merlin; BiGG Integration Tool


Description

Genome-Scale metabolic models (GEMs) are a relevant tool in systems biology for in silico strain optimisation and drug discovery. An easier way to reconstruct a model is to use available GEMs as templates to create the initial draft, which can be curated up until a simulation-ready model is obtained. This approach is implemented in merlin's BiGG Integration Tool, which reconstructs models from existing GEMs present in the BiGG Models database. This study aims to assess draft models generated using models from BiGG as templates for three distinct organisms, namely, Streptococcus thermophilus, Xylella fastidiosa and Mycobacterium tuberculosis. Several draft models were reconstructed using the BiGG Integration Tool and different templates (all, selected and random). The variability of the models was assessed using the reactions and metabolic functions associated with the model's genes. This analysis showed that, even though the models shared a significant portion of reactions and metabolic functions, models from different organisms are still differentiated. Moreover, there also seems to be variability among the templates used to generate the draft models to a lower extent. This study concluded that the BiGG Integration Tool provides a fast and reliable alternative for draft reconstruction for bacteria.

Document Type Conference paper
Language English
Contributor(s) Universidade do Minho
facebook logo  linkedin logo  twitter logo 
mendeley logo

Related documents

No related documents