Network pharmacology in food-medicine homology: AI-driven decoding of multi-target synergy from molecular networks to precision health

Abstract

Network pharmacology provides a transformative framework for decoding multi-target, system-level mechanisms of the food-medicine homology (FMH) substances, overcoming the limitations of reductionist approaches by integrating multi-omics data, computational modeling, and network analysis. Central to this paradigm is the “Network Targets” theory, which conceptualizes therapeutic intervention as the reconfiguration of disease-associated biological networks rather than the modulation of isolated single targets. Artificial intelligence accelerates this process by enabling high-dimensional data integration, predictive modeling of synergistic combinations, and the identification of active constituents. This review outlines the key databases and computational tools that operationalize network pharmacology in FMH research and systematically categorizes their applications, including material screening, ingredient identification, synergy analysis, quality standard establishment, safety assessment, formula optimization, functional food discovery, and personalized recommendation, supported by experimental validation across numerous FMH items. Despite the challenges in data standardization and dynamic modeling, the integration of multi-omics, dynamic networks, and centralized repositories will further advance the field. Ultimately, network pharmacology will bridge traditional FMH wisdom with contemporary mechanistic rigor, positioning FMH as the cornerstone of precision nutrition and preventive medicine.

Keywords

Artificial intelligence / Food-medicine homology / Network pharmacology / Network targets

References

[1] Li S, Zhang B. Traditional Chinese medicine network pharmacology: theory, methodology and application. Chin J Nat Med 2013; 11(2): 110-120.

[2] Zhang P, Zhang D, Zhou W, et al. Network pharmacology: towards the artificial intelligence—based precision traditional Chinese medicine. Brief Bioinform 2023; 25(1): bbad518.

[3] Zhong HN, Tang ZQ, Li YF, et al. The Evolution and Significance of Medicine and Food Homology. Acupunct Herb Med 2024; 4(1): 19-35.

[4] Li S. Possible association between Chinese medicine evidence and molecular network regulation. Scientific and Technological Progress and Socio—Economic Development for the 21st Century (Upper Volume). Beijing: China Science and Technology Press; 1999: 442.

[5] Li S. Mapping ancient remedies: applying a network approach to traditional Chinese medicine. Science 2015; 350: S72-SS4.

[6] Li S, Zhang ZQ, Wu LJ, et al. Understanding ZHENG in traditional Chinese medicine in the context of neuro—endocrine—immune network. IET Syst Biol 2007; 1(1): 51-60.

[7] Liu Q, Chen Z, Wang B, et al. Leveraging network target theory for efficient prediction of drug—disease interactions: a transfer learning approach. Adv Sci (Weinh) 2025; 12(11): e2409130.

[8] Inoue N, Shibata T, Sawada R, et al. Human microbiome—based prediction of health effects of foods via machine learning. J Agric Food Chem 2025; 73(36): 22425-22435.

[9] Chen Z, Wang H, Li C, et al. Large language models in traditional Chinese medicine: a systematic review. Acupunct Herb Med 2025; 5(1): 57-67.

[10] Xia L, Li C, Zhao J, et al. Rebalancing immune homeostasis in combating disease: the impact of medicine food homology plants and gut microbiome. Phytomedicine 2025; 136: 156150.

[11] Zhou T, Zhao F. AI—empowered human microbiome research. Gut 2025. doi: 10.1136/gutjnl—2025—335946. Epub ahead of print.

[12] Tian S, Li Y, Xu J, et al. COIMMR: a computational framework to reveal the contribution of herbal ingredients against human cancer via immune microenvironment and metabolic reprogramming. Brief Bioinform 2023; 24(6): bbad346.

[13] Zhang J, Chen X, Huang L, et al. Traditional Chinese medicine + artificial intelligence: Wuzhen consensus. Acupunct Herb Med 2025; 5(2): 134-135.

[14] Zhang P, Gao C, Zhang Z, et al. Systematic inference of super—resolution cell spatial profiles from histology images. Nat Commun 2025; 16(1): 1838.

[15] Sha H, Gong F, Liu B, et al. Leveraging retrieval—augmented large language models for dietary recommendations with traditional Chinese medicine’s medicine food homology: algorithm development and validation. JMIR Med Inform 2025; 13: e75279.

[16] Wu X, Jiang R, Zhang MQ, et al. Network—based global inference of human disease genes. Mol Syst Biol 2008; 4: 189.

[17] Zhao S, Li S. Network—based relating pharmacological and genomic spaces for drug target identification. PLoS One 2010; 5(7): e11764.

[18] Li S, Xiao W. General expert consensus on the application of network pharmacology in the research and development of new traditional Chinese medicine drugs. Chin J Nat Med 2025; 23(2): 129-142.

[19] Xu HY, Zhang YQ, Liu ZM, et al. ETCM: an encyclopaedia of traditional Chinese medicine. Nucleic Acids Res 2019; 47(D1): D976-D982.

[20] Wu Y, Zhang F, Yang K, et al. SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping. Nucleic Acids Res 2019; 47(D1): D1110-D1117.

[21] Fang YC, Huang HC, Chen HH, et al. TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining. BMC Complement Altern Med 2008; 8: 58.

[22] Ru J, Li P, Wang J, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform 2014; 6: 13.

[23] Kong X, Liu C, Zhang Z, et al. BATMAN—TCM 2.0: an enhanced integrative database for known and predicted interactions between traditional Chinese medicine ingredients and target proteins. Nucleic Acids Res 2024; 52(D1): D1110-D1120.

[24] Li X, Tang Q, Meng F, et al. INPUT: an intelligent network pharmacology platform unique for traditional Chinese medicine. Comput Struct Biotechnol J 2022; 20: 1345-1351.

[25] Peng C, Sang S, Shen X, et al. In vitro anti—Helicobacter pylori activity of Syzygium aromaticum and the preliminary mechanism of action . J Ethnopharmacol 2022; 288: 114995.

[26] Dong WM, Zhang YT, Wang HM, et al. Anti—inflammatory activities of new compounds isolated from the fruits of foeniculum vulgare mill. Chem Biodivers 2025; 22(3): e202401788.

[27] Yang X, Wang Y, Gong S, et al. Integrated metabolomics and network pharmacology reveal the procoagulant mechanisms of Cirsium setosum extracts. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1247: 124335.

[28] Chen B, Sun S, Fu J, et al. Ethanol extract of Portulaca oleracea L. mitigates atherosclerosis through modulation of cholesterol efflux and uptake pathways. Front Pharmacol 2025; 16: 1550812.

[29] Liu Z, Zhang Z, Chen X, et al. Citrate and hydroxycinnamate derivatives from Mume Fructus protect LPS—injured intestinal epithelial cells by regulating the FAK/PI3K/AKT signaling pathway. J Ethnopharmacol 2023; 301: 115834.

[30] Lihong J, Defu T, Zhaohui F, et al. Mechanism underlying Fanmugua () leaf multicomponent synergistic therapy for anemia: data mining based on hematopoietic network. J Tradit Chin Med 2023; 43(3): 542-551.

[31] Orlando G, Recinella L, Chiavaroli A, et al. Water extract from inflorescences of industrial hemp futura 75 variety as a source of anti—inflammatory, anti—proliferative and antimycotic agents: results from in silico, in vitro and ex vivo studies. Antioxidants (Basel) 2020; 9(5): 437.

[32] Lin SX, Yang C, Jiang RS, et al. Flavonoid extracts of Citrus aurantium L. var. amara Engl. Promote browning of white adipose tissue in high—fat diet—induced mice. J Ethnopharmacol 2024; 324: 117749.

[33] Kong J, Xiang Q, Ge W, et al. Network pharmacology mechanisms and experimental verification of licorice in the treatment of ulcerative colitis. J Ethnopharmacol 2024; 324: 117691.

[34] Hu Y, Lei S, Yan Z, et al. Angelica dahurica regulated the polarization of macrophages and accelerated wound healing in diabetes: a network pharmacology study and in vivo experimental validation. Front Pharmacol 2021; 12: 678713.

[35] Pan J, Lu Y, Wang S, et al. Synergistic neuroprotective effects of two natural medicinal plants against CORT—induced nerve cell injury by correcting neurotransmitter deficits and inflammation imbalance. Phytomedicine 2023; 121: 155102.

[36] Li X, Wang J, Zhou J, et al. Myristica fragrans water extract modulates multiple biological processes to pre—protect anhydrous ethanol—induced gastric ulcers via Akt/JNK/Nrf2 pathway activation. J Ethnopharmacol 2025; 340: 119258.

[37] Xiang L, Bo X, Xin L, et al. Network pharmacology—based research uncovers cold resistance and thermogenesis mechanism of Cinnamomum cassia. Fitoterapia 2021; 149: 104824.

[38] Qu J, Xu X, Yang J, et al. Establishment of an efficacy—oriented quality grading framework for herbal medicines: Phyllanthus emblica as an example. J Ethnopharmacol 2025; 346: 119632.

[39] Deng X, Luo R, Lu Y, et al. Study on material basis and mechanism of the expectorant effect by Citri Sarcodactylis Fructus: integrated network pharmacology, spectrum—effect relationship, metabolomics and pharmacokinetics. J Ethnopharmacol 2025; 351: 120118.

[40] Luo J, Luo J, Wu Y, et al. Anti—obesity effects of adzuki bean saponins in improving lipid metabolism through reducing oxidative stress and alleviating mitochondrial abnormality by activating the PI3K/Akt/GSK3beta/beta—catenin signaling pathway. Antioxidants (Basel) 2024; 13(11): 1380.

[41] Zhang J, Lin D, Wu Y, et al. Blood—supplementing effect of low molecular weight peptides of E—Jiao on chemotherapy—induced myelosuppression: evaluation of pharmacological activity and identification of bioactive peptides released in vivo. Front Pharmacol 2024; 15: 1366407.

[42] Liu J, Zhang Y, Lai CJ, et al. Multitarget protective effects of JUB on abeta—induced neurotoxicity and the mechanism predication using network pharmacology analysis. J Agric Food Chem 2023; 71(51): 20724-20734.

[43] Ruan J, Li H, Lu M, et al. Bioactive triterpenes of jujube in the prevention of colorectal cancer and their molecular mechanism research. Phytomedicine 2023; 110: 154639.

[44] Wang YL, Lang DQ, Wu C, et al. Chemical composition and antibacterial and antiulcerative colitis activities of essential oil from pruni semen. J Agric Food Chem 2024; 72(2): 1096-1113.

[45] Liu P, Zeng L, Fu H, et al. Investigating the therapeutic mechanisms of honeysuckle (China) in sepsis through network pharmacology and experimental validation. Infect Drug Resist 2025; 18: 3257-3277.

[46] Meng X, Tang GY, Zhao CN, et al. Hepatoprotective effects of Hovenia dulcis seeds against alcoholic liver injury and related mechanisms investigated via network pharmacology. World J Gastroenterol 2020; 26(24): 3432-3446.

[47] Zheng Q, Chen X, Al—Ansi W, et al. Aqueous extract of wolfberry alleviates aging—related skeletal muscle dysfunction by modulating PRRs signaling pathways and enhancing DNA repair. Mol Nutr Food Res 2024; 68(17): e2400307.

[48] Liang J, Xu Y, Chen J, et al. Antioxidant aromatic compounds from Amomum villosum and target prediction of active ingredients. Bioorg Chem 2024; 147: 107375.

[49] Wang Y, Yu Z, Zhang Z, et al. Integrating metabolomics with network pharmacology to reveal the mechanism of Poria cocos in hyperuricemia treatment. J Ethnopharmacol 2025; 337(Pt 3): 118977.

[50] Wang Q, Wang XY, Tao J, et al. Exploring the potential anticancer targets and mechanistic pathways of Elsholtzia densa essential oil based on network pharmacology. J Asian Nat Prod Res 2025; 27(7): 1038-1057.

[51] Li X, Liu X, Li B, et al. Identifying the active components and mechanisms of Persicae Semen in treating androgenetic alopecia: Insights from network pharmacology and experimental evaluations. J Ethnopharmacol 2025; 347: 119755.

[52] Bai X, Zhao X, Liu K, et al. Mulberry leaf compounds and gut microbiota in Alzheimer’s disease and diabetes: a study using network pharmacology, molecular dynamics simulation, and cellular assays. Int J Mol Sci 2024; 25(7): 4062.

[53] Li X, Wang Q, Wang M, et al. Integrated metabolomics and network pharmacology revealed the key active ingredients for the treatment of ulcerative colitis in the Citrus reticulata “Dahongpao” peel. J Pharm Biomed Anal 2024; 239: 115887.

[54] Yan Z, Zhang L, Kang Y, et al. Integrating serum pharmacochemistry and network pharmacology to explore potential compounds and mechanisms of Alpiniae oxyphyllae fructus in the treatment of cellular senescence in diabetic kidney disease. Front Med (Lausanne) 2024; 11: 1424644.

[55] Qi Y, Zhou Q, Zhang Y, et al. Exploring the active components and potential mechanisms of Alpiniae oxyphyllae Fructus in treating diabetes mellitus with depression by UPLC—Q—exactive orbitrap/MS, network pharmacology and molecular docking. Metab Brain Dis 2024; 39(6): 1065-1084.

[56] Xiao X, Luo F, Fu M, et al. Evaluating the therapeutic role of selected active compounds in Plumula Nelumbinis on pulmonary hypertension via network pharmacology and experimental analysis. Front Pharmacol 2022; 13: 977921.

[57] Zheng X, Zhang Y, Xu J, et al. Exploring the underlying mechanism of Alpinia officinarum hance ameliorating diabetic gastroparesis through combining network pharmacology, molecular docking, and in vivo experimental verification. Front Biosci (Landmark Ed) 2023; 28(8): 164.

[58] Li X, Luo Z, Hu T, et al. Exploring the anti—inflammatory effects of total flavonoids from L. gracile on LPS—induced inflammation: an integrated approach combining network pharmacology, molecular docking, and experimental validation. Int Immunopharmacol 2025; 161: 115027.

[59] Elkhalifa AEO, Banu H, Khan MI, et al. Integrated network pharmacology, molecular docking, molecular simulation, and in vitro validation revealed the bioactive components in soy—fermented food products and the underlying mechanistic pathways in lung cancer. Nutrients 2023; 15(18): 3949.

[60] Tian D, Yang Y, Yu M, et al. Anti—inflammatory chemical constituents of Flos Chrysanthemi Indici determined by UPLC—MS/MS integrated with network pharmacology. Food Funct 2020; 11(7): 6340-6351.

[61] Amatjan M, Li N, He P, et al. A novel approach based on gut microbiota analysis and network pharmacology to explain the mechanisms of action of Cichorium intybus L. formula in the improvement of hyperuricemic nephropathy in rats. Drug Des Devel Ther 2023; 17: 107-128.

[62] Wang F, Chen H, Hu Y, et al. Integrated comparative metabolomics and network pharmacology approach to uncover the key active ingredients of Polygonati rhizoma and their therapeutic potential for the treatment of Alzheimer’s disease. Front Pharmacol 2022; 13: 934947.

[63] Yong C, Zhang Z, Huang G, et al. Exploring the critical components and therapeutic mechanisms of Perilla frutescens L. in the treatment of chronic kidney disease via network pharmacology. Front Pharmacol 2021; 12: 717744.

[64] Garcia PJB, Huang SK, De Castro—Cruz KA, et al. An in vitro evaluation and network pharmacology analysis of prospective anti—prostate cancer activity from perilla frutescens. Plants (Basel) 2023; 12(16): 3006.

[65] Zhang J, Zhao L, He J, et al. Protect effects of perilla seed extract and its active ingredient luteolin against inflammatory bowel disease model via the PI3K/AKT signal pathway in vivo and in vitro. Int J Mol Sci 2025; 26(8): 3564.

[66] Du H, Shao M, Xu S, et al. Integrating metabolomics and network pharmacology analysis to explore mechanism of Pueraria lobata against pulmonary fibrosis: involvement of arginine metabolism pathway. J Ethnopharmacol 2024; 332: 118346.

[67] Mao J, Li M, Wang X, et al. Exploring the mechanism of Pueraria lobata (Willd.) Ohwi in the regulation of obesity. J Ethnopharmacol 2024; 335: 118703.

[68] Zhang Y, Wen R, Ren J, et al. Exploring the mechanism of sesamin for the treatment of PM(2.5)—induced cardiomyocyte damage based on transcriptomics, network pharmacology and experimental verification. Front Pharmacol 2024; 15: 1486563.

[69] Kim Y, Oh Y, Lee H, et al. Prediction of the therapeutic mechanism responsible for the effects of Sophora japonica flower buds on contact dermatitis by network—based pharmacological analysis. J Ethnopharmacol 2021; 271: 113843.

[70] Liu J, Yang H, Liu R, et al. Investigation of the anti—lung cancer mechanisms of taraxacum officinale based on network pharmacology and multidimensional experimental validation. Pharmaceuticals (Basel) 2025; 18(5): 663.

[71] Qu J, Ke F, Liu Z, et al. Uncovering the mechanisms of dandelion against triple—negative breast cancer using a combined network pharmacology, molecular pharmacology and metabolomics approach. Phytomedicine 2022; 99: 153986.

[72] Deng P, Wang H, Xu X. Comparative analysis of chemical profiles and biological activities of essential oils derived from Torreya grandis arils and leaves: in vitro and in silico studies. Plants (Basel) 2024; 13(18): 2640.

[73] Bian Z, Zhang W, Tang J, et al. Mechanisms underlying the action of ziziphi spinosae semen in the treatment of insomnia: a study involving network pharmacology and experimental validation. Front Pharmacol 2021; 12: 752211.

[74] Zou W, Dong Y, Yang S, et al. Imperatae rhizoma—Hedyotis diffusa Willd. herbal pair alleviates nephrotic syndrome by integrating anti—inflammatory and hypolipidaemic effects. Phytomedicine 2021; 90: 153644.

[75] Cao L, Yang X, Zhao Y, et al. Effect of rhizoma phragmitis on chronic bronchitis based on network pharmacology and its mechanism (in Chinese). Pharmacol Clin Chin Mater Med 2021; 37(2): 96-103.

[76] Park N, Chung JY, Kim MH, et al. Protective effects of inhalation of essential oils from Mentha piperita leaf on tight junctions and inflammation in allergic rhinitis. Front Allergy 2022; 3: 1012183.

[77] Hu J, Pang X, Liang X, et al. Raspberry ameliorates renal fibrosis in rats with chronic kidney disease via the PI3K/Akt pathway. Phytomedicine 2025; 140: 156589.

[78] Wang X, Zhang X, Liao Q, et al. Study on the mechanism of raspberry (Rubi fructus) in treating type 2 diabetes based on UPLC—Q—exactive orbitrap MS, network pharmacology, and experimental validation. Phytochem Anal 2025; 36(3): 744-758.

[79] Nam HH, Kim JS, Lee J, et al. Pharmacological effects of Agastache rugosa against gastritis using a network pharmacology approach. Biomolecules 2020; 10(9): 1298.

[80] Niu X, Zhang J, Ni J, et al. Network pharmacology—based identification of major component of Angelica sinensis and its action mechanism for the treatment of acute myocardial infarction. Biosci Rep 2018; 38(6): BSR20180519.

[81] Yuan A, Liu C, Feng W, et al. Integrating network pharmacology, quantitative metabolic network analysis, in vitro experiments, and molecular dynamics to explore the mechanism of Angelica sinensis for regulating bone metabolism. Comb Chem High Throughput Screen 2025; 28(6): 1054-1071.

[82] Wang S, Yang J, Cai L, et al. Antioxidant effect of ethyl acetate fraction from kaempferia galanga L.: integrated phytochemical profiling, network analysis, and experimental validation. Antioxidants (Basel) 2025; 14(5): 551.

[83] Yang X, Man D, Zhao P, et al. Identification of the therapeutic mechanism of the saffron crocus on glioma through network pharmacology and bioinformatics analysis. Med Oncol 2023; 40(10): 296.

[84] Tang Y, Yang H, Yu J, et al. Network pharmacology—based prediction and experimental verification of the involvement of the PI3K/Akt pathway in the anti—thyroid cancer activity of crocin. Arch Biochem Biophys 2023; 743: 109643.

[85] Jin B, Yang B, Wang C, et al. Mechanism of volatile oil of Amomum tsao—ko Crevost et Lemaire in the treatment of acute gastritis based on network pharmacology and experimental validation (in Chinese). J Southwest Minzu Univ (Natural Science Edition) 2022; 48(6): 643-652.

[86] Jo HG, Baek CY, Kim D, et al. Network analysis, in vivo, and in vitro experiments identified the mechanisms by which Piper longum L. [Piperaceae] alleviates cartilage destruction, joint inflammation, and arthritic pain. Front Pharmacol 2023; 14: 1282943.

[87] Wang H, Li Y, Bian Y, et al. Potential hepatoprotective effects of Cistanche deserticola Y.C. Ma: integrated phytochemical analysis using UPLC—Q—TOF—MS/MS, target network analysis, and experimental assessment. Front Pharmacol 2022; 13: 1018572.

[88] Shan C, Wu Z, Xia Y, et al. Network pharmacological study and in vitro studies validation—molecular dynamics simulation of Cistanche deserticola in promoting periodontitis and bone remodeling. Int Immunopharmacol 2024; 135: 112299.

[89] Ren B, Wang M, Hao D, et al. Dendrobium officinale extract alleviates aging—induced kidney injury by inhibiting oxidative stress via the PI3K/Akt/Nrf2/HO—1 pathway. J Ethnopharmacol 2025; 352: 120156.

[90] Yang C, Li J, Luo M, et al. Unveiling the molecular mechanisms of Dendrobium officinale polysaccharides on intestinal immunity: an integrated study of network pharmacology, molecular dynamics and in vivo experiments. Int J Biol Macromol 2024; 276(Pt 2): 133859.

[91] Dong R, Zhang Y, Chen S, et al. Identification of key pharmacodynamic markers of American ginseng against heart failure based on metabolomics and zebrafish model. Front Pharmacol 2022; 13: 909084.

[92] Hua Y, Tan X, Zhang J, et al. Deciphering the pharmacological mechanism of radix astragali for allergic rhinitis through network pharmacology and experimental validation. Sci Rep 2024; 14(1): 29873.

[93] Lv F, Sun M, Qin C, et al. Study of the multitarget mechanism of Astragalus (HUANGQI) in the treatment of Alzheimer’s disease based on network pharmacology and molecular docking technology. Pharm Biol 2024; 62(1): 634-647.

[94] Chen K, Yu Y, Wang Y, et al. Systematic pharmacology and experimental validation to reveal the alleviation of astragalus membranaceus regulating ferroptosis in osteoarthritis. Drug Des Devel Ther 2024; 18: 259-275.

[95] Zhilin L, Haobo F, Juan W, et al. Investigating the therapeutic potential of Ganoderma lucidum in treating optic nerve atrophy through network pharmacology and experimental validation. Biochem Biophys Res Commun 2025; 760: 151702.

[96] Zhang Y, Yuan PP, Li PY, et al. Investigating the possible mechanism of Cornus officinalis in the therapy of ischemic stroke by UHPLC—Q—TOF—MS, network pharmacology, molecular docking, and experimental verification. J Ethnopharmacol 2025; 338(Pt 2): 119072.

[97] Sun P, Zhang R, Li X, et al. Integrating strategy of network pharmacology, molecular dynamics simulation, and experimental verification to investigate the potential mechanism of gastrodia elata against alcoholic liver injury. Foods 2025; 14(12): 2008.

[98] Liu P, Zhao Z, Zhang H, et al. A comprehensive pharmacology study reveals the molecular mechanisms underlying the antidepressant effects of Gastrodiae rhizoma. Phytomedicine 2025; 142: 156761.

[99] Huang Q, Zhang F, Liu S, et al. Systematic investigation of the pharmacological mechanism for renal protection by the leaves of Eucommia ulmoides Oliver using UPLC—Q—TOF/MS combined with network pharmacology analysis. Biomed Pharmacother 2021; 140: 111735.

[100] Xie J, Wu M, Li L, et al. Integrated bioinformatics and experimental verification to dissect the mechanisms and bioactive ingredients of Radix Rehmanniae in treating multiple sclerosis. Biochem Biophys Res Commun 2025; 763: 151790.

[101] Mo N, Zhou P, Liu F, et al. Integrating network pharmacology, molecular docking, and experimental validation to reveal the mechanism of Radix Rehmanniae in psoriasis. Medicine (Baltim) 2024; 103(43): e40211.

[102] Xie YQ, Yan FN, Yu LH, et al. Mechanism of Shashen—Maidong herb pair in treating hepatocellular carcinoma using network pharmacology and experimental validation. J Ethnopharmacol 2025; 337(Pt 3): 118954.

[103] Deng G, Liu C, Zhao J, et al. Exocarpium Citri Grandis alleviates the aggravation of NAFLD by mitigating lipid accumulation and iron metabolism disorders. J Ethnopharmacol 2023; 313(116559): 116559.

[104] Zhao X, Xiu J, Yang H, et al. Network pharmacology and bioinformatics study of six medicinal food homologous plants against colorectal cancer. Int J Mol Sci 2025; 26(3): 930.

[105] Hu Y, Zhai W, Tan D, et al. Uncovering the effects and molecular mechanism of Astragalus membranaceus (Fisch.) Bunge and its bioactive ingredients formononetin and calycosin against colon cancer: an integrated approach based on network pharmacology analysis coupled with experimental validation and molecular docking. Front Pharmacol 2023; 14: 1111912.

[106] Duan H, Wang W, Shi Y, et al. Anti—colorectal cancer actions of Glycyrrhiza uralensis Fisch. and its underlying mechanism via HPLC integration and network pharmacological approaches. Phytomedicine 2025; 138: 156370.

[107] Deng XQ, Zhang HB, Wang GF, et al. Colon—specific microspheres loaded with puerarin reduce tumorigenesis and metastasis in colitis—associated colorectal cancer. Int J Pharm 2019; 570: 118644.

[108] Villegas C, Perez R, Sterner O, et al. Curcuma as an adjuvant in colorectal cancer treatment. Life Sci 2021; 286: 120043.

[109] Guo C, Guo D, Fang L, et al. Ganoderma lucidum polysaccharide modulates gut microbiota and immune cell function to inhibit inflammation and tumorigenesis in colon. Carbohydr Polym 2021; 267: 118231.

[110] Mao J, Wang G, Yang L, et al. Combined network pharmacology and molecular docking to verify the treatment of type 2 diabetes with Pueraria lobata radix and Salviae miltiorrhizae radix. Comput Math Methods Med 2023; 2023: 9150324.

[111] Hou B, Ma P, Yang X, et al. In silico prediction and experimental validation to reveal the protective mechanism of Puerarin against excessive extracellular matrix accumulation through inhibiting ferroptosis in diabetic nephropathy. J Ethnopharmacol 2024; 319(Pt 2): 117281.

[112] Deniz OG, Soyturk H, Him A, et al. Luteolin mitigates hippocampal damage in a rat model of streptozotocin—induced diabetes. Biomol Biomed 2025; 25: 2364-2377.

[113] Zhang H, Kang J, Guo W, et al. An optimal medicinal and edible Chinese herbal formula attenuates particulate matter—induced lung injury through its anti—oxidative, anti—inflammatory and anti—apoptosis activities. Chin Herb Med 2023; 15(3): 407-420.

[114] Yu YY, Fu HQ, Du HY, et al. Overview of research on the application of medicine food homologous bioactive ingredients to functional constipation. Food Medicine Homology, 2025; 2(4): 9420057.

[115] Yang X, Li L, Yan Y, et al. Investigation of the pharmacodynamic components of gastrodia elata blume for treatment of type 2 diabetes mellitus through HPLC, bioactivity, network pharmacology and molecular docking. Int J Mol Sci 2024; 25(19): 10498.

[116] Xu YH, Chen J. Discovery of quality markers of Phyllanthus emblica by integrating chromatographic fingerprint, serum pharmacochemistry and network pharmacology. J Pharm Biomed Anal 2024; 249: 116346.

[117] Wang L, Chen Y, Liu Y, et al. Traditional Chinese medicine for cerebral ischemia—reperfusion injury prevention: molecular mechanisms and future perspectives. Am J Chin Med 2025; 53(4): 999-1026.

[118] Duan X, Fan X, Jiang H, et al. Herb—drug interactions in oncology: pharmacodynamic/pharmacokinetic mechanisms and risk prediction. Chin Med 2025; 20(1): 107.

[119] Ma BL, Ma YM. Pharmacokinetic herb—drug interactions with traditional Chinese medicine: progress, causes of conflicting results and suggestions for future research. Drug Metab Rev 2016; 48(1): 1-26.

[120] Wang T, Zhang T, Chen X, et al. Herb—drug interaction of Astragali Radix based on in vitro incubation and pharmacokinetic assessment. BMC Complement Med Ther 2025; 25(1): 339.

[121] Yuan S, Zhou Z, Jin X, et al. Enhancing herbal medicine—drug interaction prediction using large language models. IEEE J Biomed Health Inform 2025; 29(10): 6971-6981.

[122] Li Y, Wang X, Yang Z, et al. A new approach for optimizing empirical prescriptions of famous physicians based on network target: taking Qingluo Decoction as an example. Zhongguo Zhong Yao Za Zhi 2022; 47(19): 5264-5273.

[123] Oh KK, Gupta H, Min BH, et al. Elucidation of prebiotics, probiotics, postbiotics, and target from gut microbiota to alleviate obesity via network pharmacology study. Cells 2022; 11(18): 2903.

[124] Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024; 74(3): 229-263.

[125] Liu Z, Guo F, Wang Y, et al. BATMAN—TCM: a bioinformatics analysis tool for molecular mechanism of traditional Chinese medicine. Sci Rep 2016; 6: 21146.

[126] Li G, Kim HJ, Pendyala S, et al. Sceptic: pseudotime analysis for time—series single—cell sequencing and imaging data. Genome Biol 2025; 26(1): 209.

[127] Zhang P, Mourad R, Xiang Y, et al. A dynamic time order network for time—series gene expression data analysis. BMC Syst Biol 2012; 6(Suppl 3): S9.

[128] Li L, Xu Y, Yan L, et al. Dynamic network biomarker factors orchestrate cell—fate determination at tipping points during hESC differentiation. Innovation (Camb). 2023; 4(1): 100364.

[129] Sarkar S, Sinha SK, Levine H, et al. Anticipating critical transitions in epithelial—hybrid—mesenchymal cell—fate determination. Proc Natl Acad Sci U S A 2019; 116(52): 26343-26352.

[130] Zou M, Conzen SD. A new dynamic Bayesian network (DBN) approach for identifying gene regulatory networks from time course microarray data. Bioinformatics 2005; 21(1): 71-79.

[131] Habiba SU, Choi HJ, Munni YA, et al. Neurotrophic effects of foeniculum vulgare ethanol extracts on hippocampal neurons: role of anethole in neurite outgrowth and synaptic development. Int J Mol Sci 2024; 25(23): 12701.