TY - JOUR
T1 - Conditional flux balance analysis toolbox for python
T2 - application to research metabolism in cyclic environments
AU - Páez-Watson, Timothy
AU - Hernández Medina, Ricardo
AU - Vellekoop, Loek
AU - van Loosdrecht, Mark C.M.
AU - Wahl, S. Aljoscha
PY - 2024
Y1 - 2024
N2 - We present py_cFBA, a Python-based toolbox for conditional flux balance analysis (cFBA). Our toolbox allows for an easy implementation of cFBA models using a well-documented and modular approach and supports the generation of Systems Biology Markup Language models. The toolbox is designed to be user-friendly, versatile, and freely available to non-commercial users, serving as a valuable resource for researchers predicting metabolic behaviour with resource allocation in dynamic-cyclic environments.
AB - We present py_cFBA, a Python-based toolbox for conditional flux balance analysis (cFBA). Our toolbox allows for an easy implementation of cFBA models using a well-documented and modular approach and supports the generation of Systems Biology Markup Language models. The toolbox is designed to be user-friendly, versatile, and freely available to non-commercial users, serving as a valuable resource for researchers predicting metabolic behaviour with resource allocation in dynamic-cyclic environments.
UR - http://www.scopus.com/inward/record.url?scp=85213459986&partnerID=8YFLogxK
U2 - 10.1093/bioadv/vbae174
DO - 10.1093/bioadv/vbae174
M3 - Article
AN - SCOPUS:85213459986
SN - 2635-0041
VL - 4
JO - Bioinformatics Advances
JF - Bioinformatics Advances
IS - 1
M1 - vbae174
ER -