AuCoMe: inferring and comparing metabolisms across heterogeneous sets of annotated genomes
| hal.structure.identifier | Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss] | |
| dc.contributor.author | BELCOUR, Arnaud | |
| hal.structure.identifier | Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss] | |
| dc.contributor.author | GOT, Jeanne | |
| hal.structure.identifier | Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss] | |
| dc.contributor.author | AITE, Méziane | |
| hal.structure.identifier | Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M] | |
| dc.contributor.author | DELAGE, Ludovic | |
| hal.structure.identifier | Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M] | |
| dc.contributor.author | COLLEN, Jonas | |
| hal.structure.identifier | Pleiade, from patterns to models in computational biodiversity and biotechnology [PLEIADE] | |
| dc.contributor.author | FRIOUX, Clémence | |
| hal.structure.identifier | Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M] | |
| dc.contributor.author | LEBLANC, Catherine | |
| hal.structure.identifier | Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M] | |
| dc.contributor.author | DITTAMI, Simon | |
| hal.structure.identifier | Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss] | |
| dc.contributor.author | BLANQUART, Samuel | |
| hal.structure.identifier | Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M] | |
| dc.contributor.author | MARKOV, Gabriel | |
| hal.structure.identifier | Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss] | |
| dc.contributor.author | SIEGEL, Anne | |
| dc.description.abstractEn | Comparative analysis of Genome-Scale Metabolic Networks (GSMNs) may yield important information on the biology, evolution, and adaptation of species. However, it is impeded by the high heterogeneity of the quality and completeness of structural and functional genome annotations, which may bias the results of such comparisons. To address this issue, we developed AuCoMe-a pipeline to automatically reconstruct homogeneous GSMNs from a heterogeneous set of annotated genomes without discarding available manual annotations. We tested AuCoMe with three datasets, one bacterial, one fungal, and one algal, and demonstrated that it successfully reduces technical biases while capturing the metabolic specificities of each organism. Our results also point out shared metabolic traits and divergence points among evolutionarily distant species, such as algae, underlining the potential of AuCoMe to accelerate the broad exploration of metabolic evolution across the tree of life. | |
| dc.language.iso | en | |
| dc.subject.en | Bioinformatics | |
| dc.subject.en | Proteins genomics | |
| dc.subject.en | metabolism | |
| dc.subject.en | metabolic evolution | |
| dc.subject.en | genomes | |
| dc.subject.en | systems biology | |
| dc.title.en | AuCoMe: inferring and comparing metabolisms across heterogeneous sets of annotated genomes | |
| dc.type | Document de travail - Pré-publication | |
| dc.identifier.doi | 10.1101/2022.06.14.496215 | |
| dc.subject.hal | Informatique [cs]/Bio-informatique [q-bio.QM] | |
| hal.identifier | hal-03778267 | |
| hal.version | 1 | |
| hal.origin.link | https://hal.archives-ouvertes.fr//hal-03778267v1 | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=BELCOUR,%20Arnaud&GOT,%20Jeanne&AITE,%20M%C3%A9ziane&DELAGE,%20Ludovic&COLLEN,%20Jonas&rft.genre=preprint |
Fichier(s) constituant ce document
| Fichiers | Taille | Format | Vue |
|---|---|---|---|
|
Il n'y a pas de fichiers associés à ce document. |
|||