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A protocol for generating a high-quality genome-scale metabolic reconstruction

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A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information

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A Whole-Cell Computational Model Predicts Phenotype from Genotype

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Bacterial metabolism and pathogenesis intimate intertwining: time for metabolic modelling to come into action

Nogales, J., & Garmendia, J. (2021) · Microbial Biotechnology · doi:10.1111/1751-7915.13942 · Cited by 12

Genome-Scale Reconstruction of Microbial Dynamic Phenotype: Successes and Challenges

Panikov, N. S. (2021) · Microorganisms · doi:10.3390/microorganisms9112352 · Cited by 15

In silico encounters: harnessing metabolic modelling to understand plant–microbe interactions

Feierabend, M., & Töpfer, N. (2025) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuaf030 · Cited by 14

Genome-scale metabolic modeling in antimicrobial pharmacology

Zhu, Y., Zhao, J., & Li, J. (2022) · Engineering Microbiology · doi:10.1016/j.engmic.2022.100021 · Cited by 14

An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter

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Genome-wide identification of overexpression and downregulation gene targets based on the sum of covariances of the outgoing reaction fluxes

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Revealing the dynamics and mechanisms of bacterial interactions in cheese production with metabolic modelling

Lecomte, M., Cao, W., Aubert, J., Sherman, D. J., Falentin, H., Frioux, C., & Labarthe, S. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.02.014 · Cited by 19

Improving genome-scale metabolic models of incomplete genomes with deep learning

Boer, M. D., Melkonian, C., Zafeiropoulos, H., Haas, A. F., Garza, D. R., & Dutilh, B. E. (2024) · iScience · doi:10.1016/j.isci.2024.111349 · Cited by 14

A Computational Toolbox to Investigate the Metabolic Potential and Resource Allocation in Fission Yeast

Grigaitis, P., Grundel, D. A. J., van Pelt‐KleinJan, E., Isaku, M., Xie, G., Mendoza, S. N., Teusink, B., & van Heerden, J. H. (2022) · mSystems · doi:10.1128/msystems.00423-22 · Cited by 14

When biodiversity preservation meets biotechnology: The challenge of developing synthetic microbiota for resilient sustainable crop production

Fagorzi, C., Passeri, I., Cangioli, L., Vaccaro, F., & Mengoni, A. (2023) · Journal of Sustainable Agriculture and Environment · doi:10.1002/sae2.12038 · Cited by 14

In Silico Modeling of Metabolic Pathways in Probiotic Microorganisms for Functional Food Biotechnology

Baimakhanova, B. B., САДАНОВ, А. К., Ратникова, И. А., Baimakhanova, G. B., Orasymbet, S., Amitova, A. A., Aitkaliyeva, G., & Kakimova, A. B. (2025) · Fermentation · doi:10.3390/fermentation11080458 · Cited by 13

Interrogation of Essentiality in the Reconstructed Haemophilus influenzae Metabolic Network Identifies Lipid Metabolism Antimicrobial Targets: Preclinical Evaluation of a FabH β-Ketoacyl-ACP Synthase Inhibitor

López-López, N., León, D. S., de Castro, S., Díez‐Martínez, R., Iglesias-Bexiga, M., Camarasa, M., Menéndez, M., Nogales, J., & Garmendia, J. (2022) · mSystems · doi:10.1128/msystems.01459-21 · Cited by 12

Construction and application of high-quality genome-scale metabolic model of Zymomonas mobilis to guide rational design of microbial cell factories

Wu, Y., Yuan, Q., Yang, Y., Liu, D., Yang, S., & Ma, H. (2023) · Synthetic and Systems Biotechnology · doi:10.1016/j.synbio.2023.07.001 · Cited by 13

CFSA: Comparative flux sampling analysis as a guide for strain design

van Rosmalen, R. P., Paz, S. M., Duman‐Özdamar, Z. E., & Diez, M. S. (2024) · Metabolic Engineering Communications · doi:10.1016/j.mec.2024.e00244 · Cited by 13

Unveiling the link between phytoplankton molecular physiology and biogeochemical cycling via genome-scale modeling

Régimbeau, A., Aumont, O., Bowler, C., Guidi, L., Jackson, G. A., Karsenti, E., Mémery, L., Tagliabue, A., & Eveillard, D. (2025) · Science Advances · doi:10.1126/sciadv.adq3593 · Cited by 23

Dynamic models for metabolomics data integration

Lakrisenko, P., & Weindl, D. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.100358 · Cited by 14

Genome-Scale Modeling Specifies the Metabolic Capabilities of Rhizophagus irregularis

Wendering, P., & Nikoloski, Z. (2022) · mSystems · doi:10.1128/msystems.01216-21 · Cited by 12

Systems Biology of Aromatic Compound Catabolism in Facultative Anaerobic Aromatoleum aromaticum EbN1 T

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PangenomeNet: a pan-genome-based network reveals functional modules on antimicrobial resistome for Escherichia coli strains

Her, H.-L., Lin, P. T., & Wu, Y. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04459-z · Cited by 13

Whole‐genome sequencing and genome‐scale metabolic modeling of Chromohalobacter canadensis 85B to explore its salt tolerance and biotechnological use

Enuh, B. M., Yaman, B. N., Tarzi, C., Çelik, P. A., Mutlu, M. B., & Angione, C. (2022) · MicrobiologyOpen · doi:10.1002/mbo3.1328 · Cited by 11

Multiscale metabolic engineering in biological lignin valorization

Liu, R.-Y., Li, B., Yuan, Y., & Liu, Z. (2025) · The Innovation · doi:10.1016/j.xinn.2025.100993 · Cited by 14

COBREXA.jl: constraint-based reconstruction and exascale analysis

Kratochvíl, M., Heirendt, L., Wilken, S. E., Pusa, T., Arreckx, S., Noronha, A., van Aalst, M., Satagopam, V., Ebenhöh, O., Schneider, R., et al. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab782 · Cited by 12

From Observational to Actionable: Rethinking Omics in Biologics Production

Masson, H. O., Karottki, K. J. L. C., Tat, J., Hefzi, H., & Lewis, N. E. (2023) · Trends in biotechnology · doi:10.1016/j.tibtech.2023.03.009 · Cited by 12

Understanding Antimicrobial Resistance Using Genome-Scale Metabolic Modeling

Alonso-Vásquez, T., Fondi, M., & Perrin, E. (2023) · Antibiotics · doi:10.3390/antibiotics12050896 · Cited by 14

Co‐Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction

Xue, B., Liu, Y., Yang, C., Liu, H., Yuan, Q., Wang, S., & Su, H. (2023) · Advanced Science · doi:10.1002/advs.202306662 · Cited by 12

Recent advances in metabolic engineering–integration of in silico design and experimental analysis of metabolic pathways

Shimizu, H., & Toya, Y. (2021) · Journal of Bioscience and Bioengineering · doi:10.1016/j.jbiosc.2021.08.002 · Cited by 12

In silico and in vivo analyses reveal key metabolic pathways enabling the fermentative utilization of glycerol in Escherichia coli

Clomburg, J. M., Cintolesi, Á., & González, R. (2021) · Microbial Biotechnology · doi:10.1111/1751-7915.13938 · Cited by 12

A benchmark of optimization solvers for genome-scale metabolic modeling of organisms and communities

Machado, D. (2024) · mSystems · doi:10.1128/msystems.00833-23 · Cited by 13

Physicochemical Perspective of Biological Heterogeneity

Kwapiszewska, K. (2024) · ACS Physical Chemistry Au · doi:10.1021/acsphyschemau.3c00079 · Cited by 11

A long-term growth stable Halomonas sp. deleted with multiple transposases guided by its metabolic network model Halo-ecGEM

Zhang, L., Ye, J., Li, G., Park, H., Luo, H., Lin, Y., Li, S., Yang, W., Guan, Y., Wu, F., et al. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.06.004 · Cited by 11

Impact of trace metal supplementation on anaerobic biological methanation under hydrogen and carbon dioxide starvation

Ghiotto, G., Bernardini, N. D., Orellana, E., Fiorito, G., Cenci, L., Kougias, P., Campanaro, S., & Treu, L. (2025) · npj Biofilms and Microbiomes · doi:10.1038/s41522-025-00649-2 · Cited by 11

A Guide to Metabolic Network Modeling for Plant Biology

Rao, X., & Liu, W. (2025) · Plants · doi:10.3390/plants14030484 · Cited by 13

Microbial Pathway Thermodynamics: Stoichiometric Models Unveil Anabolic and Catabolic Processes

Ebenhöh, O., Ebeling, J., Meyer, R., Pohlkotte, F., & Nies, T. (2024) · Life · doi:10.3390/life14020247 · Cited by 11

Expanded gut microbial genomes from Chinese populations reveal population-specific genomic features related to human physiological traits

Dong, Q., Ma, B., Zhou, X., Huang, P., Gao, M., Yang, S., Jiao, Y., Zhou, Y., Shi, Z., Deng, Q., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01566-x · Cited by 14

The view of microbes as energy converters illustrates the trade-off between growth rate and yield

Wilken, S. E., Frazão, V. V., Saadat, N. P., & Ebenhöh, O. (2021) · Biochemical Society Transactions · doi:10.1042/bst20200977 · Cited by 9

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Zúñiga, C., Tibocha‐Bonilla, J. D., & Betenbaugh, M. J. (2021) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2021.06.024 · Cited by 10

Maximization of non-idle enzymes improves the coverage of the estimated maximal in vivo enzyme catalytic rates in Escherichia coli

Xu, R., Razaghi‐Moghadam, Z., & Nikoloski, Z. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab575 · Cited by 11

Development of in silico strategies to photoautotrophically produce poly-β-hydroxybutyrate (PHB) by cyanobacteria

Testa, R. L., Delpino, C., Estrada, V., & Díaz, M. S. (2022) · Algal Research · doi:10.1016/j.algal.2021.102621 · Cited by 10

Bacterial Pangenome: A Review on the Current Strategies, Tools and Applications

Golchha, N. C., Nighojkar, A., & Nighojkar, S. (2024) · Medinformatics · doi:10.47852/bonviewmedin42022496 · Cited by 9

Network approach to understand biological systems: From single to multilayer networks

Chaudhuri, S., & Srivastava, A. (2022) · Journal of Biosciences · doi:10.1007/s12038-022-00285-4 · Cited by 9

Engineering Gut Symbionts: A Way to Promote Bee Growth?

Sattayawat, P., Inwongwan, S., Noirungsee, N., Li, J., Guo, J. L., & Disayathanoowat, T. (2024) · Insects · doi:10.3390/insects15050369 · Cited by 9

A compact model of Escherichia coli core and biosynthetic metabolism

Corrao, M., He, H., Liebermeister, W., Noor, Ε., & Bar‐Even, A. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013564 · Cited by 9

Modelling hCDKL5 Heterologous Expression in Bacteria

Fondi, M., Gonzi, S., Dziurzyński, M., Turano, P., Ghini, V., Calvanese, M., Colarusso, A., Lauro, C., Parrilli, E., & Tutino, M. L. (2021) · Metabolites · doi:10.3390/metabo11080491 · Cited by 8

Robustness and Complexity of Directed and Weighted Metabolic Hypergraphs

Traversa, P., de Arruda, G. F., Vázquez, A., & Moreno, Y. (2023) · Entropy · doi:10.3390/e25111537 · Cited by 11

HOLI-1-to-3: Transient-Enhanced Holistic Image-to-3D Generation

Shen, S. S., Xia, S., Peng, X., Wang, Z., Zhu, Y., Li, S., & Jingyi Yu, A. (2024) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2024.3463875 · Cited by 8

Genome streamlining of Pseudomonas putida B6-2 for bioremediation

Fan, S., Ren, H., Fu, X., Kong, X., Wu, H., & Lv, Z. (2024) · mSystems · doi:10.1128/msystems.00845-24 · Cited by 9

CarveAdornCurate: a versatile cloud-based platform for constructing multiscale metabolic models

Cheng, Y., Yu, W., Bi, X., Liu, Y., Li, J., Du, G., Chen, J., Lv, X., & Liu, L. (2025) · Trends in biotechnology · doi:10.1016/j.tibtech.2025.01.011 · Cited by 8

Metabolic modeling of host-microbe interactions

Srinak, N., Krüger, F., Kaleta, C., & Taubenheim, J. (2025) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2025.10.006 · Cited by 8

mergem: merging, comparing, and translating genome-scale metabolic models using universal identifiers

Hari, A., Zarrabi, A., & Lobo, D. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae010 · Cited by 8

A novel explainable kinetic model for two-stage fermentation profile

Huang, X., Liu, C., & Lin, Y. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.152745 · Cited by 8

Development of computational models using omics data for the identification of effective cancer metabolic biomarkers

Lee, S. M., & Kim, H. U. (2021) · Molecular Omics · doi:10.1039/d1mo00337b · Cited by 8

Systematic diet composition swap in a mouse genome-scale metabolic model reveals determinants of obesogenic diet metabolism in liver cancer

Clasen, F., Nunes, P. M., Bidkhori, G., Bah, N. K., Boeing, S., Shoaie, S., & Anastasiou, D. (2023) · iScience · doi:10.1016/j.isci.2023.106040 · Cited by 8

Extracting functionally accurate context-specific models of Atlantic salmon metabolism

Molversmyr, H., Øyås, O., Rotnes, F., & Vik, J. O. (2023) · npj Systems Biology and Applications · doi:10.1038/s41540-023-00280-x · Cited by 8

Multi-HGNN: Multi-modal hypergraph neural networks for predicting missing reactions in metabolic networks

Huang, Y., Liang, X., Lin, T., & Liu, J. (2025) · Information Sciences · doi:10.1016/j.ins.2025.121960 · Cited by 8

Data-driven revolution of enzyme catalysis from the perspective of reactions, pathways, and enzymes

Liu, T., Zhai, S., Zhan, X., & Siu, S. W. I. (2025) · Cell Reports Physical Science · doi:10.1016/j.xcrp.2025.102466 · Cited by 7

Metabolic network reconstruction of Euglena gracilis: Current state, challenges, and applications

Inwongwan, S., Pekkoh, J., Pumas, C., & Sattayawat, P. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1143770 · Cited by 7

Targeting tumour metabolism in melanoma to enhance response to immune checkpoint inhibition: A balancing act

Tiersma, J. F., Evers, B., Bakker, B. M., Reijngoud, D., de Bruyn, M., de Jong, S., & Jalving, M. (2024) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2024.102802 · Cited by 8

Insights on the Advancements of In Silico Metabolic Studies of Succinic Acid Producing Microorganisms: A Review with Emphasis on Actinobacillus succinogenes

Dessie, W., Wang, Z., Luo, X., Wang, M., & Qin, Z. (2021) · Fermentation · doi:10.3390/fermentation7040220 · Cited by 7

Practical sampling of constraint-based models: Optimized thinning boosts CHRR performance

Jadebeck, J. F., Wiechert, W., & Nöh, K. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011378 · Cited by 8

Towards modeling genome-scale knowledge in the global oceanPreprint

Régimbeau, A., Aumont, O., Bowler, C., Guidi, L., Jackson, G. A., Karsenti, E., Mémery, L., Tagliabue, A., & Eveillard, D. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.23.568447 · Cited by 7

Challenges and Future Perspectives for Scaling Up Bio-Based Carbonate Mineralization Technologies

Miller, E. J., Hodo, W., Tingle, J. S., & Saracho, A. C. (2025) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.5c03941 · Cited by 8

Overall biomass yield on multiple nutrient sources

Golan, O., Gampp, O., Eckert, L., & Sauer, U. (2025) · npj Systems Biology and Applications · doi:10.1038/s41540-025-00497-y · Cited by 6

The unraveling of balanced complexes in metabolic networks

Langary, D., Küken, A., & Nikoloski, Z. (2023) · Scientific Reports · doi:10.1038/s41598-023-32666-6 · Cited by 5

Genome-scale metabolic modelling in antimicrobial pharmacology: Present and future

Tao, J., Lin, Y.-W., Zhong, L., Zhu, Y., Yao, X., Aichem, M., Schreiber, F., Zhao, J., & Li, J. (2025) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2025.115672 · Cited by 5

Pan-reactome analysis of Streptomyces strains reveals association and disconnection between primary and secondary metabolism

Lee, B. T., Mohite, O. S., Kwon, M. S., Kang, H., Weber, T., Lee, S. Y., & Kim, H. U. (2025) · Metabolic Engineering · doi:10.1016/j.ymben.2025.08.005 · Cited by 5

Microbiome metabolic modeling as a tool for innovation in fermented foods

Karimi, E., Tap, J., Champomier‐Vergès, M., & Chaillou, S. (2025) · Current Opinion in Food Science · doi:10.1016/j.cofs.2025.101368 · Cited by 5

Natural color biofactories: advancing the spectrum of pigment production in phototrophic microbes

Noreña-Caro, D., Uribe, L. F. P., Morales, M., Canto-Encalada, G., Álvarez-Láinez, M., & Zúñiga, C. (2025) · FEMS Microbes · doi:10.1093/femsmc/xtaf019 · Cited by 6

Systematically exploring yeast metabolism through retrobiosynthesis and deep learning

Wu, K., Liu, H., Zhou, R., Sun, M., Mao, R., Jiang, Y., Kerkhoven, E. J., Chen, Y., Nielsen, J., Tang, H., et al. (2026) · Nature Catalysis · doi:10.1038/s41929-026-01523-w · Cited by 6

A dual-scale fused hypergraph convolution-based hyperedge prediction model for predicting missing reactions in genome-scale metabolic networks

Huang, W., Yang, F., Zhang, Q., & Liu, J. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae383 · Cited by 5

Understanding disease-associated metabolic changes in human colonic epithelial cells using the iColonEpithelium metabolic reconstruction

Jiang, B., Quinn-Bohmann, N., Diener, C., Nathan, V. B., Han-Hallett, Y., Reddivari, L., Gibbons, S. M., & Baloni, P. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013253 · Cited by 6

A geometric deep learning framework for genome-wide prediction of enzyme turnover number

Pan, T., Cui, X., Koh, H. Y., Bi, Y., Wang, X., Zhang, Y., Hu, S., Webb, G. I., Kurgan, L., Zhang, G., et al. (2026) · Genome biology · doi:10.1186/s13059-026-03986-3 · Cited by 8

Applications of Microbial Consortia and Microbiome Interactions for Augmenting Sustainable Agrobiology

Niranjan, V., Setlur, A. S., Skariyachan, S., & Chandrashekar, K. (2023) · Microorganisms for sustainability · doi:10.1007/978-981-19-9570-5_13 · Cited by 5

Control analysis in the identification of key enzymes driving metabolic adaptations: Towards drug target discovery

de Atauri, P., Foguet, C., & Cascante, M. (2023) · Biosystems · doi:10.1016/j.biosystems.2023.104984 · Cited by 5

Genome sequencing and metabolic network reconstruction of a novel sulfur-oxidizing bacterium Acidithiobacillus Ameehan

Wu, P., Yuan, Q., Cheng, T., Han, Y., Zhao, W., Liao, X., Wang, L., Cai, J., He, Q., Guo, Y., et al. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1277847 · Cited by 5

Systems Biology on Acetogenic Bacteria for Utilizing C1 Feedstocks

Song, Y., Bae, J., Shin, J., Jin, S., Kang, S., Lee, H., Cho, S., & Cho, B. (2022) · Advances in biochemical engineering, biotechnology · doi:10.1007/10_2021_199 · Cited by 5

A digital twin of bacterial metabolism during cheese productionPreprint

Lecomte, M., Cao, W., Aubert, J., Sherman, D. J., Falentin, H., Frioux, C., & Labarthe, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.05.539417 · Cited by 5

A constraint-based framework to reconstruct interaction networks in microbial communitiesPreprint

Oftadeh, O., Sahin, A., Vayena, E., & Vassily Hatzimanikatis, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.30.577913 · Cited by 5

Enhancing genome-scale metabolic models with kinetic data: resolving growth and citramalate production trade-offs in Escherichia coli

Lázaro, J., Wongprommoon, A., Júlvez, J., & Oliver, S. G. (2024) · Bioinformatics Advances · doi:10.1093/bioadv/vbaf166 · Cited by 5

Artificial design of the genome: from sequences to the 3D structure of chromosomes

Wang, J., Xie, Z., Cui, Y., Li, B., & Yuan, Y. (2024) · Trends in biotechnology · doi:10.1016/j.tibtech.2024.08.012 · Cited by 4

A hierarchy of metabolite exchanges in metabolic models of microbial species and communities

Wedmark, Y. K., Vik, J. O., & Øyås, O. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012472 · Cited by 4

Multi-omics analysis uncovers the transcriptional regulatory mechanism of magnesium Ions in the synthesis of active ingredients in Sophora tonkinensis

Zhu, Q., Zhou, P.-C., Fan, Z.-T., Wei, F., Qin, S., Wang, J., Liang, Y., Chen, L., & Wei, K. (2024) · Scientific Reports · doi:10.1038/s41598-024-76575-8 · Cited by 4

Recent advances in genome-scale modeling of proteome allocation

Dahal, S., Zhao, J., & Yang, L. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.04.002 · Cited by 4

A Beginner’s Guide to the COBRA Toolbox

Navid, A. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1585-0_15 · Cited by 4

Cyanobacterial Bioinoculants for Abiotic Stress Management in the Changing Climate Scenario

Thapa, S., Vishwakarma, R., & Nagaraju, Y. (2023) · Springer eBooks · doi:10.1007/978-981-99-2973-3_8 · Cited by 4

Modular Dynamic Biomolecular Modelling with Bond Graphs: The Unification of Stoichiometry, Thermodynamics, Kinetics and DataPreprint

Gawthrop, P. J., Pan, M., & Crampin, E. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.24.436792 · Cited by 4

Unified knowledge-driven network inference from omics dataPreprint

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Genomic and taxonomic characterization of Niallia pakistanensis sp. nov. NCCP-28T: a novel antibiotic-resistant and heavy-metal-tolerant bacterium isolated from the legume rhizosphere in Pakistan

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