BioISO: an objective-oriented application for assisting the curation of genome-scale metabolic models
| Autor: | Eugénio C. Ferreira, Fernando Cruz, Oscar Dias, João Capela, Miguel Rocha |
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| Rok vydání: | 2021 |
| Předmět: |
0303 health sciences
Computer science business.industry In silico Systems biology Machine learning computer.software_genre Manual curation Flux balance analysis 03 medical and health sciences 0302 clinical medicine Artificial intelligence business computer 030217 neurology & neurosurgery Biological network 030304 developmental biology |
| Popis: | As the reconstruction of Genome-Scale Metabolic Models becomes standard practice in systems biology, the number of organisms having at least one metabolic model at the genome-scale is peaking at an unprecedented scale. The automation of several laborious tasks, such as gap-finding and gap-filling, allowed to develop GSMMs for poorly described organisms. However, such models’ quality can be compromised by the automation of several steps, which may lead to erroneous phenotype simulations.The Biological networks constraint-based In Silico Optimization (BioISO) is a computational tool aimed at accelerating the reconstruction of Genome-Scale Metabolic Models. This tool facilitates the manual curation steps by reducing the large search spaces often met when debugging in silico biological models. BioISO uses a recursive relation-like algorithm and Flux Balance Analysis to evaluate and guide debugging of in silico phenotype simulations. The potential of BioISO to guide the debugging of model reconstructions was showcased using GSMMs available in literature and compared with the results of two other state-of-the-art gap-filling tools (Meneco and fastGapFill). Furthermore, BioISO was used as Meneco’s gap-finding algorithm to reduce the number of proposed solutions (reaction sets) for filling the gaps.BioISO was implemented as a webserver available at https://bioiso.bio.di.uminho.pt; and integrated into merlin as a plugin. BioISO’s implementation as a Python™ package can also be retrieved from https://github.com/BioSystemsUM/BioISO. |
| Databáze: | OpenAIRE |
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