Result: dingo : a Python package for metabolic flux sampling

Title:
dingo : a Python package for metabolic flux sampling
Authors:
Chalkis, Apostolos, Fisikopoulos, Vissarion, Tsigaridas, Elias, Zafeiropoulos, Haris
Contributors:
GeomScale Org., National and Kapodistrian University of Athens (NKUA), OUtils de Résolution Algébriques pour la Géométrie et ses ApplicatioNs (OURAGAN), Institut de Mathématiques de Jussieu - Paris Rive Gauche (IMJ-PRG (UMR_7586)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Centre Inria de Sorbonne Université, Centre Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratory of Molecular Bacteriology [KU Leuven], Catholic University of Leuven = Katholieke Universiteit Leuven (KU Leuven), My institution (Inria) has paid the publication costs for this article to be in open access
Source:
Bioinformatics Advances. 4(1)
Publisher Information:
CCSD; Oxford academic, 2024.
Publication Year:
2024
Collection:
collection:CNRS
collection:INRIA
collection:INRIA-ROCQ
collection:INSMI
collection:IMJ
collection:TESTALAIN1
collection:INRIA2
collection:SORBONNE-UNIVERSITE
collection:SORBONNE-UNIV
collection:SU-SCIENCES
collection:UNIV-PARIS
collection:UNIVERSITE-PARIS
collection:UP-SCIENCES
collection:SU-TI
collection:ALLIANCE-SU
collection:SUPRA_MATHS_INFO
Subject Terms:
Metabolic networks, Python Library, Sampling, Flux model, [SDV.BBM.BM]Life Sciences [q-bio], Biochemistry, Molecular Biology, Molecular biology
Original Identifier:
HAL: hal-04549128
Document Type:
Journal article<br />Journal articles
Language:
English
ISSN:
2635-0041
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1093/bioadv/vbae037
DOI:
10.1093/bioadv/vbae037
Access URL:
https://inria.hal.science/hal-04549128
https://inria.hal.science/hal-04549128v1/document
https://inria.hal.science/hal-04549128v1/file/2023.06.18.545486v1.full.pdf
Rights:
info:eu-repo/semantics/OpenAccess
URL: http://creativecommons.org/licenses/by/
Accession Number:
edshal.hal.04549128v1
Database:
HAL

Further Information

We present dingo, a Python package that supports a variety of methods to sample from the flux space of metabolic models, based on state-of-the-art random walks and rounding methods. For uniform sampling, dingo’s sampling methods provide significant speed-ups and outperform existing software. Indicatively, dingo can sample from the flux space of the largest metabolic model up to now (Recon3D) in less than a day using a personal computer, under several statistical guarantees; this computation is out of reach for other similar software. In addition, dingo supports common analysis methods, such as flux balance analysis and flux variability analysis, and visualization components. dingo contributes to the arsenal of tools in metabolic modelling by enabling flux sampling in high dimensions (in the order of thousands).