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Current Protocols in Plant Biology|March 25, 2020
Supervised Learning of Gene Regulatory NetworksZahra Razaghi-Moghadam, Zoran NikoloskiBioinformatics (Oxford, England)|November 27, 2020
GeneReg: a constraint-based approach for design of feasible metabolic engineering strategies at the gene levelZahra Razaghi-Moghadam, Zoran NikoloskiNPJ Systems Biology and Applications|July 2, 2020
Supervised learning of gene-regulatory networks based on graph distance profiles of transcriptomics dataZahra Razaghi-Moghadam, Zoran NikoloskiScientific Reports|December 11, 2021
Identification of flux trade-offs in metabolic networksSeirana Hashemi, Zahra Razaghi-Moghadam, Zoran NikoloskiBulletin of Mathematical Biology|August 30, 2017
A Systems Biology Approach to Understanding Alcoholic Liver Disease Molecular Mechanism: The Development of Static and Dynamic ModelsLeila Shafaghati, Zahra Razaghi-Moghadam, Javad MohammadnejadMetabolic Engineering|February 17, 2024
Prediction and integration of metabolite-protein interactions with genome-scale metabolic modelsMahdis Habibpour, Zahra Razaghi-Moghadam, Zoran NikoloskiPlos Computational Biology|September 18, 2023
Maximizing multi-reaction dependencies provides more accurate and precise predictions of intracellular fluxes than the principle of parsimonySeirana Hashemi, Zahra Razaghi-Moghadam, Zoran NikoloskiScientific Reports|April 21, 2021
Reaction lumping in metabolic networks for application with thermodynamic metabolic flux analysisLea Seep, Zahra Razaghi-Moghadam, Zoran NikoloskiNAR Genomics and Bioinformatics|September 4, 2024
Machine learning of metabolite-protein interactions from model-derived metabolic phenotypesMahdis Habibpour, Zahra Razaghi-Moghadam, Zoran NikoloskiBioinformatics (Oxford, England)|August 6, 2021
Maximization of non-idle enzymes improves the coverage of the estimated maximal in vivo enzyme catalytic rates in Escherichia coliRudan Xu, Zahra Razaghi-Moghadam, Zoran NikoloskiPageof 4