Constraint-based modelling predicts metabolic signatures of low and high-grade serous ovarian cancer

Research output: Contribution to journal › Article › peer-review

Original language	Undefined
Article number	96
Journal	npj Systems Biology and Applications
Volume	10
DOIs	https://doi.org/10.1038/s41540-024-00418-5
Publication status	Published - 24 Aug 2024

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title = "Constraint-based modelling predicts metabolic signatures of low and high-grade serous ovarian cancer",

author = "Meeson, \{Kate E.\} and Jean-Marc Schwartz",

year = "2024",

month = aug,

day = "24",

doi = "10.1038/s41540-024-00418-5",

language = "Undefined",

volume = "10",

journal = "npj Systems Biology and Applications",

issn = "2056-7189",

publisher = "Springer Nature",

}

TY - JOUR

T1 - Constraint-based modelling predicts metabolic signatures of low and high-grade serous ovarian cancer

AU - Meeson, Kate E.

AU - Schwartz, Jean-Marc

PY - 2024/8/24

Y1 - 2024/8/24

UR - https://doi.org/10.1038/s41540-024-00418-5

U2 - 10.1038/s41540-024-00418-5

DO - 10.1038/s41540-024-00418-5

M3 - Article

SN - 2056-7189

VL - 10

JO - npj Systems Biology and Applications

JF - npj Systems Biology and Applications

M1 - 96

ER -