RBApy: Extending resource allocation modeling to eukaryotes in complex environments
Abstract
Motivation: Resource allocation modeling—as the Resource Balance Analysis (RBA) framework— provides a way to understand and predict how limited cellular resources (e.g., energy, proteins, etc.) in cells are distributed among competing cell processes within a limited cellular space. Currently, resource allocation modeling for any eukaryotes remains limited due to the lack of software capable of generating calibrated RBA models for these types of cells, unlike prokaryotes, which benefit from the software tools RBApy, RBAtools and the RBAml format for model encoding. Results: Here we extended the RBA toolkit (RBApy, RBAtools and RBAml) to account for specific aspects of eukaryotic cells growing in complex environments such as varying temperature, light or nutritional conditions. We used them to generate and simulate RBA models of both prokaryotic (Escherichia coli) and eukaryotic (Arabidopsis thaliana) cells for varying temperatures. The resulting models show excellent prediction capabilities when benchmarked against published experimental datasets. The upgraded RBA toolkit will pave the way to creating, calibrating and running resource allocation models for crops, livestock or humans for a wide range of medical, biotechnological or agricultural applications in the future.
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BibTeX
@article{bodeit2026rbapy,
title = {{RBApy: Extending resource allocation modeling to eukaryotes in complex environments}},
author = {Oliver Bodeit and Nadia Bessoltane-Bentahar and Delphine Charif and Anaghim Temtem and Olivier Inizan and Anne Goelzer},
journal = {Bioinformatics Advances},
year = {2026},
month = sep,
doi = {10.1093/bioadv/vbag276},
url = {https://hal.inrae.fr/hal-05585881v2},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - RBApy: Extending resource allocation modeling to eukaryotes in complex environments
AU - Oliver Bodeit
AU - Nadia Bessoltane-Bentahar
AU - Delphine Charif
AU - Anaghim Temtem
AU - Olivier Inizan
AU - Anne Goelzer
PY - 2026
DA - 2026/09/29
JO - Bioinformatics Advances
DO - 10.1093/bioadv/vbag276
UR - https://hal.inrae.fr/hal-05585881v2
AB - Motivation: Resource allocation modeling—as the Resource Balance Analysis (RBA) framework— provides a way to understand and predict how limited cellular resources (e.g., energy, proteins, etc.) in cells are distributed among competing cell processes within a limited cellular space. Currently, resource allocation modeling for any eukaryotes remains limited due to the lack of software capable of generating calibrated RBA models for these types of cells, unlike prokaryotes, which benefit from the software tools RBApy, RBAtools and the RBAml format for model encoding. Results: Here we extended the RBA toolkit (RBApy, RBAtools and RBAml) to account for specific aspects of eukaryotic cells growing in complex environments such as varying temperature, light or nutritional conditions. We used them to generate and simulate RBA models of both prokaryotic (Escherichia coli) and eukaryotic (Arabidopsis thaliana) cells for varying temperatures. The resulting models show excellent prediction capabilities when benchmarked against published experimental datasets. The upgraded RBA toolkit will pave the way to creating, calibrating and running resource allocation models for crops, livestock or humans for a wide range of medical, biotechnological or agricultural applications in the future.
SN - 2635-0041
ER -