Systems Biology of Metabolism

Gene Ontology: tool for the unification of biology

Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206

Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation

Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197

Tissue-based map of the human proteome

Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286

A human gut microbial gene catalogue established by metagenomic sequencing

MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624

Diet rapidly and reproducibly alters the human gut microbiome

David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., et al. (2014) · Nature · doi:10.1038/nature12820 · Cited by 10,100

A metagenome-wide association study of gut microbiota in type 2 diabetes

Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., Liang, S., Zhang, W., Guan, Y., Shen, D., et al. (2012) · Nature · doi:10.1038/nature11450 · Cited by 6,762

Exploring the metabolic and genetic control of gene expression on a genomic scale.

Derisi, J., Iyer, V., & Brown, P. (1997) · Science · doi:10.1126/science.278.5338.680 · Cited by 4,832

Functional interactions between the gut microbiota and host metabolism

Tremaroli, V., & Bäckhed, F. (2012) · Nature · doi:10.1038/nature11552 · Cited by 4,387

Resveratrol improves health and survival of mice on a high-calorie diet

Baur, J. A., Pearson, K. J., Price, N. L., Jamieson, H. A., Lerin, C., Kalra, A., Prabhu, V. V., Allard, J. S., Lopez-Lluch, G., Lewis, K., et al. (2006) · Nature · doi:10.1038/nature05354 · Cited by 4,290

Systems biology: a brief overview

Kitano, H. (2002) · Science · doi:10.1126/science.1069492 · Cited by 4,265

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

Model-assisted CRISPRi/a library screening reveals central carbon metabolic targets for enhanced recombinant protein production in yeast

Chen, X., Li, F., Li, X., Otto, M., Chen, Y., & Siewers, V. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.11.010 · Cited by 14

Big data in yeast systems biology

Yu, R., & Nielsen, J. (2019) · FEMS Yeast Research · doi:10.1093/femsyr/foz070 · Cited by 17

The Untargeted Metabolomics Reveals Differences in Energy Metabolism in Patients with Different Subtypes of Ischemic Stroke

Li, X., Li, J., Yu, F., Feng, X., Luo, Y., Liu, Z., Zhao, T., & Xia, J. (2024) · Molecular Neurobiology · doi:10.1007/s12035-023-03884-w · Cited by 13

Interactive Metabolism, a simple and robust active learning tool that improves the biochemistry knowledge of undergraduate students

França, V. C. P. L. A. D., & Campos, W. F. (2021) · AJP Advances in Physiology Education · doi:10.1152/advan.00042.2020 · Cited by 15

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

Becker, P., Kirstein, S., Wünsch, D., Koblitz, J., Buschen, R., Wöhlbrand, L., Bunk, B., Hinrichs, C., Kaltenhäuser, S., Lehmann, J., et al. (2022) · mSystems · doi:10.1128/msystems.00685-22 · Cited by 14

Model predictive control of a fermenter using dynamic flux balance analysis coupled with convolutional neural networks

Dehkordi, M. B., Pishvaie, M. R., & Vafa, E. (2023) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2023.108444 · Cited by 12

Advances in Research on Pig Salivary Analytes: A Window to Reveal Pig Health and Physiological Status

Zheng, L., Shi, L., Wu, X., Hu, P., Zhang, B., Han, X., Wang, K., Li, X., Yang, F., Wang, Y., et al. (2024) · Animals · doi:10.3390/ani14030374 · Cited by 12

Multiomics metabolic and epigenetics regulatory network in cancer: A systems biology perspective

Wang, X., Dong, Y., Zheng, Y., & Chen, Y. (2021) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2021.05.008 · Cited by 13

Bioinformatics and system biology approaches to identify molecular pathogenesis of polycystic ovarian syndrome, type 2 diabetes, obesity, and cardiovascular disease that are linked to the progression of female infertility

Hossain, M. A., Amin, M. A., Hasan, M. I., Sohel, M., Ahammed, M. A., Mahmud, S. M. H., Rahman, M. R., & Rahman, M. H. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.100960 · Cited by 13

Genome-scale models as a vehicle for knowledge transfer from microbial to mammalian cell systems

Strain, B., Morrissey, J., Antonakoudis, A., & Kontoravdi, C. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.02.011 · Cited by 13

In-Cell NMR Approach for Real-Time Exploration of Pathway Versatility: Substrate Mixtures in Nonengineered Yeast

Sannelli, F., Jensen, P. R., & Meier, S. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.3c00225 · Cited by 12

Yeast systems biology in understanding principles of physiology underlying complex human diseases

Yu, R., & Nielsen, J. (2019) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2019.11.021 · Cited by 14

Oomycete metabolism is highly dynamic and reflects lifestyle adaptationsPreprint

Rodenburg, S. Y. A., de Ridder, D., Govers, F., & Seidl, M. F. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.12.941195 · Cited by 12

Serum metabolomic analyses reveal the potential metabolic biomarkers for prediction of amatoxin poisoning

Liu, Y., Li, S., Yang, F., Zhang, Y., Ouyang, J., Li, S., Wang, J., Tan, L., & Zou, L. (2023) · Toxicon · doi:10.1016/j.toxicon.2023.107153 · Cited by 11

Microbial cell factories for bio-based isoprenoid production to replace fossil resources

Kang, M., Yoon, S., Kwon, M., & Kim, S.-W. (2024) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2023.100502 · Cited by 11

Identification of a novel signature based on macrophage-related marker genes to predict prognosis and immunotherapeutic effects in hepatocellular carcinoma

Su, Y., Xue, C., Gu, X., Wang, W., Sun, Y., Zhang, R., & Li, L. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1176572 · Cited by 12

Combined In-Cell NMR and Simulation Approach to Probe Redox-Dependent Pathway Control

Jensen, P. R., Matos, M. R. A., Sonnenschein, N., & Meier, S. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b00660 · Cited by 11

Sevoflurane Alters Serum Metabolites in Elders and Aging Mice and Increases Inflammation in Hippocampus

Wang, T., Wu, X., Zhao, X., Li, J., Yu, J., Sheng, M., Gao, M., Cao, Y., Wang, J., Guo, X., et al. (2024) · Journal of Inflammation Research · doi:10.2147/jir.s448959 · Cited by 10

Oomycete Metabolism Is Highly Dynamic and Reflects Lifestyle Adaptations

Rodenburg, S. Y. A., de Ridder, D., Govers, F., & Seidl, M. F. (2024) · Molecular Plant-Microbe Interactions · doi:10.1094/mpmi-12-23-0200-r · Cited by 22

Gains and losses of metabolic function inferred from a phylotranscriptomic analysis of algae

Goh, F. Q. Y., Jeyakani, J., Tipthara, P., Cazenave‐Gassiot, A., Ghosh, R., Bogard, N., Yeo, Z., Wong, G. K., Melkonian, M., Wenk, M. R., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-46869-3 · Cited by 10

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

Standardization of Human Metabolic Stoichiometric Models: Challenges and Directions

Pantziri, M. D. A., & Klapa, M. I. (2022) · Frontiers in Systems Biology · doi:10.3389/fsysb.2022.899980 · Cited by 10

The Central Metabolism Model of Anopheles gambiae: A Tool for Understanding Malaria Vector Biology

Adedeji, E. O., Ogunlana, O. O., Fatumo, S., Aromolaran, O., Beder, T., Koenig, R., & Adebiyi, E. F. (2023) · Springer eBooks · doi:10.1007/978-3-031-33370-5_16 · Cited by 12

Network pharmacology combined with metabolomics to explore the mechanism for Lonicerae Japonicae flos against respiratory syncytial virus

Ding, J., Li, J., Zhang, Z., Du, Y., Liu, Y., Wang, P., & Du, H. (2023) · BMC Complementary Medicine and Therapies · doi:10.1186/s12906-023-04286-0 · Cited by 9

Modeling for understanding and engineering metabolism

Nielsen, J., & Petranović, D. (2025) · QRB Discovery · doi:10.1017/qrd.2025.1 · Cited by 11

An observation study of urinary biomarker exploratory in Alzheimer's disease using high‐resolution mass spectrometry

Zhang, Q., Wu, S., Liu, X., Yang, J. J., Dong, X. W., Zhou, Y., Chen, J., Li, Y., & Yang, J. (2022) · Biomedical Chromatography · doi:10.1002/bmc.5421 · Cited by 9

The metabolite-controlled ubiquitin conjugase Ubc8 promotes mitochondrial protein import

Rödl, S., den Brave, F., Räschle, M., Kizmaz, B., Lenhard, S., Groh, C., Becker, H., Zimmermann, J., Morgan, B., Richling, E., et al. (2022) · Life Science Alliance · doi:10.26508/lsa.202201526 · Cited by 12

Precise metabolic modeling in post-omics era: accomplishments and perspectives

Kong, Y., Chen, H., Huang, X., Chang, L., Yang, B. K., & Chen, W. (2024) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2024.2390089 · Cited by 9

Investigating the Evolution and Development of Biological Systems from the Perspective of Thermo-Kinetics and Systems Theory

Boojari, M. A. (2020) · Origins of Life and Evolution of Biospheres · doi:10.1007/s11084-020-09601-0 · Cited by 9

Challenges to Ensure a Better Translation of Metabolic Engineering for Industrial Applications

Daboussi, F., & Lindley, N. D. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2617-7_1 · Cited by 9

Integrated analyses of the methylome and transcriptome to unravel sex differences in the perirenal fat from suckling lambs

Fonseca, P. A. D. S., Alonso-García, M., Pelayo, R., Marina, H., Esteban‐Blanco, C., Mateo, J., Gutiérrez‐Gil, B., Arranz, J. J., & Suárez‐Vega, A. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.1035063 · Cited by 9

Metabolomics: State-of-the-Art Technologies and Applications on Drosophila melanogaster

An, P. N. T., & Fukusaki, E. (2018) · Advances in experimental medicine and biology · doi:10.1007/978-981-13-0529-0_14 · Cited by 9

An Introduction to the Mathematical Modeling in the Study of Cancer Systems Biology

Alameddine, A. K., Conlin, F. T., & Binnall, B. J. (2018) · Cancer Informatics · doi:10.1177/1176935118799754 · Cited by 9

Unraveling metabolic pathways and key genes in Alzheimer’s, type 2 diabetes, and estrogen dysregulation among aging women: a systems biology approach

Chowdhury, M. R., Kumar, V., & Deepa, V. S. (2024) · Journal of Proteins and Proteomics · doi:10.1007/s42485-024-00157-5 · Cited by 8

Unveiling the Molecular Mechanisms of Glioblastoma through an Integrated Network-Based Approach

Kaynar, A., Kim, W., Ceyhan, A. B., Zhang, C., Uhlén, M., Türkez, H., Shoaie, S., & Mardinoğlu, A. (2024) · Biomedicines · doi:10.3390/biomedicines12102237 · Cited by 8

An enzyme activation network reveals extensive regulatory crosstalk between metabolic pathways

Zubaidi, S. M. A., Nasar, M. I., Notebaart, R. A., Ralser, M., & Alam, M. T. (2025) · Molecular Systems Biology · doi:10.1038/s44320-025-00111-7 · Cited by 11

A Strategy for Uncovering the Serum Metabolome by Direct-Infusion High-Resolution Mass Spectrometry

Sun, X., Jia, Z., Zhang, Y., Zhao, X., Zhao, C., Lu, X., & Xu, G. (2023) · Metabolites · doi:10.3390/metabo13030460 · Cited by 8

Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets

Angarita-Rodríguez, A., González‐Giraldo, Y., Rubio-Mesa, J. J., Aristizábal-Pachón, A. F., Pinzón, A. M., & González, J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms25010365 · Cited by 8

Multi-Omics Approaches for Liver Reveal the Thromboprophylaxis Mechanism of Aspirin Eugenol Ester in Rat Thrombosis Model

Tao, Q., Ma, N., Fan, L., Ge, W., Zhang, Z., Liu, X., Li, J., & Yang, Y. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25042141 · Cited by 8

MicrobiomeNet: exploring microbial associations and metabolic profiles for mechanistic insights

Lu, Y. P., Hui, F., Zhou, G., & Xia, J. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae944 · Cited by 9

Population-Based Parameter Identification for Dynamical Models of Biological Networks with an Application to Saccharomyces cerevisiae

Węglarz‐Tomczak, E., Tomczak, J. M., Eiben, A. E., & Brul, S. (2021) · Processes · doi:10.3390/pr9010098 · Cited by 8

Constraint-based modeling of yeast mitochondria reveals the dynamics of protein import and iron-sulfur cluster biogenesis

Malina, C., Bartolomeo, F. D., Kerkhoven, E. J., & Nielsen, J. (2021) · iScience · doi:10.1016/j.isci.2021.103294 · Cited by 12

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

The Synthetic Microbiology Caucus : from abstract ideas to turning microbes into cellular machines and back

Huang, W. E., & Nikel, P. I. (2018) · Microbial Biotechnology · doi:10.1111/1751-7915.13337 · Cited by 7

Understanding methanol metabolism through systems biology: advances and future perspectives

Wang, H., Bai, F., Lu, H., & Zhou, Y. J. (2025) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2025.103370 · Cited by 7

The identification of novel stroke-related sphingolipid biomarkers using UPLC-MS/MS

Yang, Z., Deng, X., Zhu, J., Chen, S., Jiao, C., & Ruan, Y. (2023) · Clinica Chimica Acta · doi:10.1016/j.cca.2023.117652 · Cited by 7

Synthetic Biology Approaches for the Production of Isoprenoids in Escherichia coli

Tian, H., Zada, B., Singh, B. H., Wang, C., & Kim, S.-W. (2019) · Elsevier eBooks · doi:10.1016/b978-0-444-64085-7.00013-7 · Cited by 7

How do cancer cells replenish their fuel supply?

Alameddine, A. K., Conlin, F. T., Binnall, B. J., Alameddine, Y. A., & Alameddine, K. O. (2018) · Cancer Reports · doi:10.1002/cnr2.1003 · Cited by 6

Design and Implementation of a Tool to Assess Students’ Understanding of Metabolic Pathways Dynamics and Regulation

Villafañe, S. M., Minderhout, V., Heyen, B. J., Lewis, J. E., Manley, A., Murray, T. A., Tienson-Tseng, H. L., & Loertscher, J. A. (2021) · CBE—Life Sciences Education · doi:10.1187/cbe.20-04-0078 · Cited by 7

Merging traditional practices and modern technology through computational plant breeding

Yoosefzadeh-Najafabadi, M. (2025) · PLANT PHYSIOLOGY · doi:10.1093/plphys/kiaf355 · Cited by 6

Our natural “makeup” reveals more than it hides: Modeling the skin and its microbiome

Hussan, J. R., & Hunter, P. J. (2020) · WIREs Mechanisms of Disease · doi:10.1002/wsbm.1497 · Cited by 7

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

Impact of Influenza A Virus Infection on Growth and Metabolism of Suspension MDCK Cells Using a Dynamic Model

Ramos, J. R. C., Bissinger, T., Genzel, Y., & Reichl, U. (2022) · Metabolites · doi:10.3390/metabo12030239 · Cited by 6

Computational biology predicts metabolic engineering targets for increased production of 102 valuable chemicals in yeastPreprint

Domenzain, I., Lu, Y. P., Shi, J., Lu, H., & Nielsen, J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.31.526512 · Cited by 6

Evidence of antagonistic predictive effects of miRNAs in breast cancer cohorts through data-driven networks

Miglioli, C., Bakalli, G., Orso, S., Karemera, M., Molinari, R., Guerrier, S., & Mili, N. (2022) · Scientific Reports · doi:10.1038/s41598-022-08737-5 · Cited by 5

Features extracted using tensor decomposition reflect the biological features of the temporal patterns of human blood multimodal metabolome

Fujita, S., Karasawa, Y., Hironaka, K., Taguchi, Y., & Kuroda, S. (2023) · PLoS ONE · doi:10.1371/journal.pone.0281594 · Cited by 5

Metabolomics as a promising technology for investigating external therapy of traditional Chinese medicine: A review

Yang, X., He, M., Tang, Q., Cao, J., Wei, Z., Li, T., & Sun, M. (2024) · Medicine · doi:10.1097/md.0000000000040719 · Cited by 5

Multi-omics: An Opportunity to Dive into Systems Biology

dos Santos, E. A. F., Cruz, E. C. S., Ribeiro, H. C., Barbosa, L. D., Zandonadi, F. D. S., & Sussulini, A. (2020) · Brazilian Journal of Analytical Chemistry · doi:10.30744/brjac.2179-3425.rv-03-2020 · Cited by 6

Recon8D: A metabolic regulome network from oct-omics and machine learningPreprint

Schildcrout, R., Smith, K., Bhowmick, R., Lu, Y., Menon, S., Kapadia, M., Kurtz, E., Coffeen-Vandeven, A., Nelakuditi, S., & Chandrasekaran, S. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.17.608400 · Cited by 5

LC-MS/MS metabolomic profiling of the protective butylphthalide effect in cerebral ischemia/reperfusion mice

Zheng, Y., Zhao, F., Hu, Y., Yan, F., Tian, Y., Wang, R., Huang, Y., Zhong, L., Luo, Y., & Ma, Q. (2023) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2023.107347 · Cited by 4

Comprehensive Plasma Metabolome for Identification of Novel Biomarkers of Acute Myocardial Infarction

Liu, J., Yu, Y., Lu, Q., Zhang, S., & Li, J. (2025) · MedComm · doi:10.1002/mco2.70303 · Cited by 4

Progress based on a multi-omics research strategy in the biosynthesis and modernization of active ingredients of Herpetospermum pedunculosum seeds

Zheng, Y., Zhao, S., Zhang, M., Yang, L., Wu, X., Tan, R., & Jiang, H. (2024) · Fitoterapia · doi:10.1016/j.fitote.2024.106113 · Cited by 4

Novel Insights About Precision Fermentation

de Almeida, E. L. M., Ventorim, R. Z., Dias, R. G., Ferreira, M. A. D. M., Villas-Bôas, S. G., & da Silveira, W. B. (2024) · Springer eBooks · doi:10.1007/978-3-031-72000-0_6 · Cited by 5

Mechanism of P-Hydroxy Benzyl Alcohol Against Cerebral Ischemia Based on Metabonomics Analysis

Xiao, T., Yu, X., Tao, J., Tan, J., Zhao, Z., Zhang, C., & Duan, X. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26010317 · Cited by 4

GEMCAT—a new algorithm for gene expression-based prediction of metabolic alterations

Sharma, S. A., Sauter, R., Hotze, M., Prowatke, A. M. P., Niere, M., Kipura, T., Egger, A.-S., Thedieck, K., Kwiatkowski, M., Ziegler, M., et al. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf003 · Cited by 4

Co-substrate utilisation in “Candidatus Accumulibacter” enhances metabolic fitness in dynamic environments

Páez-Watson, T., Jansens, C., van Loosdrecht, M. C. M., & Roy, S. (2025) · Water Research · doi:10.1016/j.watres.2025.124401 · Cited by 4

Modeling and Simulation of Batch Sugarcane Alcoholic Fermentation Using the Metabolic Model

Acorsi, R. L., Giovanni, M. Y. G. D., Olivo, J. E., & Andrade, C. M. G. (2022) · Fermentation · doi:10.3390/fermentation8020082 · Cited by 4

The mechanisms governing mouse embryonic palate mesenchymal cells’ proliferation associated with atRA-induced cleft palate in mice: insights from integrated transcriptomic and metabolomic analyses

Yu, Z.-L., Song, S.-X., Wang, G., Zhang, Y.-J., Zhang, Y.-X., Wu, Y., Liu, H., Zhang, Y.-W., & Liu, X.-Z. (2023) · Archives of Toxicology · doi:10.1007/s00204-023-03534-z · Cited by 4

Improvement in the prediction power of an astrocyte genome-scale metabolic model using multi-omic data

Angarita-Rodríguez, A., Mejía, N. M., González, J., Papin, J. A., Aristizábal-Pachón, A. F., & Pinzón, A. M. (2025) · Frontiers in Systems Biology · doi:10.3389/fsysb.2024.1500710 · Cited by 4

Systems metabolic engineering: an integrated approach for future environmental biotechnology

Panagiotidou, E., & Theodosiou, E. (2026) · Biotechnology for the Environment · doi:10.1186/s44314-026-00042-z · Cited by 5

Insights into the response and tolerance mechanisms of Papiliotrema laurentii to acetic acid stress by RNA-seq and genome-scale metabolic modeling analysis

de Almeida, E. L. M., & da Silveira, W. B. (2025) · Biochemical Engineering Journal · doi:10.1016/j.bej.2025.109634 · Cited by 3

Staphylococcus epidermidis RP62A’s Metabolic Network: Validation and Intervention Strategies

Guil, F., Sánchez-Cid, G., & García, J. M. (2022) · Metabolites · doi:10.3390/metabo12090808 · Cited by 3

Integrated bioinformatics analysis reveals the function and prognostic value of OSBPL3 in hepatocellular carcinoma

Su, Y., Chen, X., Gu, X., Sun, Y., Zhang, R., & Li, L. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e17223 · Cited by 3

Large Flux Supply of NAD(H) under Aerobic Conditions by Candida glycerinogenes

Wang, M., Jiang, D., Lu, X., Zong, H., & Zhuge, B. (2024) · ACS Synthetic Biology · doi:10.1021/acssynbio.4c00030 · Cited by 3

The role of bacterial metabolism in human gut colonization

Muñoz‐Cazalla, A., de Quinto, I., Álvaro-Llorente, L., Rodríguez-Beltrán, J., & Herencias, C. (2024) · International Microbiology · doi:10.1007/s10123-024-00550-6 · Cited by 3

Discovery of a Therapeutic Agent for Glioblastoma Using a Systems Biology-Based Drug Repositioning Approach

Kaynar, A., Özcan, M., Li, X., Türkez, H., Zhang, C., Uhlén, M., Shoaie, S., & Mardinoğlu, A. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25147868 · Cited by 3

Biotechnology

Kumar, S., Bhatt, P., & Mutturi, S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818593-3.00009-9 · Cited by 4

Integrated Translation Framework for Endocrine Disruptors in the area of Computational Toxicology

Kumar, V., Deepika, D., & Sharma, R. P. (2020) · Royal Society of Chemistry eBooks · doi:10.1039/9781839160738-00080 · Cited by 3

A probabilistic and context-dependent cell culture modelling framework for regulatory toxicology

Madorran, E. (2026) · Frontiers in Toxicology · doi:10.3389/ftox.2026.1765753 · Cited by 2

Integrated serum metabolomics and lipidomics for identifying metabolic changes in rheumatoid arthritis

Zhu, H.-H., Ruan, Z.-H., Zhang, Z.-X., Fang, X., & Ye, D. Q. (2026) · Metabolomics · doi:10.1007/s11306-026-02447-z · Cited by 2

Cognition as a global biological process

Just, B. B., & de Farías, S. T. (2026) · Biosystems · doi:10.1016/j.biosystems.2026.105851 · Cited by 3

Integrative proteomics and metabolomics analysis of non‐observable acute effect level PM2.5 induced accumulative effects in AC16 cells

Nan, B., Sun, X., Yang, S., Huang, Q., & Shen, H. (2023) · Journal of Applied Toxicology · doi:10.1002/jat.4500 · Cited by 3

Nutrigenomics of lipid supplementation in ruminants and pigs

Amills, M., Clop, A., & Óvilo, C. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817105-9.00003-3 · Cited by 2

Redesigning Spent Media from Cell Culture Bioprocess to Feed New Bacterial Fermentations

Lynch, C. D., Jordan, L., & O’Connell, D. J. (2021) · Cell engineering · doi:10.1007/978-3-030-79871-0_5 · Cited by 2

Deep Characterization of Serum Metabolome Based on the Segment-Optimized Spectral-Stitching Direct-Infusion Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Approach

Sun, X., Xia, Y., Zhao, X., Wang, X., Zhang, Y., Jia, Z., Zheng, F., Li, Z., Zhang, X., Zhao, C., et al. (2023) · Analytical Chemistry · doi:10.1021/acs.analchem.2c04995 · Cited by 2

Metabolic constraints on nitrogen fixation by rhizobia in legume nodulesPreprint

Schulte, C. C. M., Borah, K., Wheatley, R. M., Terpolilli, J. J., Saalbach, G., Crang, N., de Groot, D. H., Ratcliffe, R. G., Kruger, N. J., Papachristodoulou, A., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.16.431433 · Cited by 2

NAFPD exacerbation by hyperlipidemia combined with hyperuricemia: a pilot rat experiment in lipidomics

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Double-Weighted Bayesian Model Combination for Metabolomics Data Description and Prediction

Troisi, J., Lombardi, M., Trotta, A., Abenante, V., Ingenito, A., Palmieri, N., Richards, S. M., Symes, S. J. K., & Cavallo, P. (2025) · Metabolites · doi:10.3390/metabo15040214 · Cited by 1

Harnessing the power: the role of dissimilatory metal-reducing bacteria in microbial fuel cells

Chakraborty, S., Chandra, S., Pandit, S., Raj, S., Gill, H. S., Sharma, K. R., Bhattacharya, D., Nag, M., & Lahiri, D. (2025) · Archives of Microbiology · doi:10.1007/s00203-025-04319-x · Cited by 1

Model-guided chemical environment and metabolic network design to couple pathways with cell fitness

von Koch, N. K., Tenkanen, T., Castillo, S., Vidgren, V., Koponen, T., Krogerus, K., Penttilä, M. E., & Jouhten, P. (2025) · Metabolic Engineering Communications · doi:10.1016/j.mec.2025.e00267 · Cited by 1

Model-driven exploration of lactose and galactose metabolism via an oxidoreductive pathway in Sungouiella intermedia for cell factory applications

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Systematic perturbation of cultures of K. phaffii by carbon co-feeding show gene signatures associated with production of recombinant proteins

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Transcriptome-informed metabolic modeling reveals astrocyte-specific vulnerabilities in mild cognitive impairment and Alzheimer’s disease progression

Angarita-Rodríguez, A., Vargas-López, V., Pinzón, A., Sandoval-Hernandez, A., Kang, K., Li, L., Papin, J., Rozo, P. J. P., Aristizábal, A., & González, J. (2026) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2026.1816121 · Cited by 1

De novo synthesis of large-scale metabolic pathways for natural products and their optimization strategies

Jiang, J., Dai, J.-L., Chen, H., Jiang, J., & Zhao, Q.-Z. (2026) · Bioresource Technology · doi:10.1016/j.biortech.2026.135370 · Cited by 1

Rewriting the symphony of life with synthetic metabolism – can enzymes play music?

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Intracellular Flux Prediction of Recombinant Escherichia coli Producing Gamma-Aminobutyric Acid

Bae, S. H., Sim, M. S., Jeong, K. J., He, D. N., Kwon, I., Kim, T., Kim, H. U., & Choi, J. (2024) · Journal of Microbiology and Biotechnology · doi:10.4014/jmb.2312.12022 · Cited by 1

System Biology Approaches for Nutrition Research

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Towards organism-level systems biology by next-generation genetics and whole-organ cell profiling

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Chameleon microRNAs in breast cancer: their elusive role as regulatory factors in cancer progressionPreprint

Miglioli, C., Bakalli, G., Orso, S., Karemera, M., Molinari, R., Guerrier, S., & Mili, N. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.15.422846 · Cited by 1

Background

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Thermodynamics-based Significance Ranking of Candidates for Metabolomics

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Synthesizing Systems Biology Knowledge from Omics Using Genome‐Scale Models

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Quantitative modeling of human metabolism: A call for a community effort

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From Gene Expression to Metabolic Fluxes

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