{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T10:28:31Z","timestamp":1786357711781,"version":"build-2736575974"},"reference-count":66,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2026,8,9]],"date-time":"2026-08-09T00:00:00Z","timestamp":1786233600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ICAR- National Institute of Veterinary Epidemiology & Disease Informatics","award":["5600119"],"award-info":[{"award-number":["5600119"]}]},{"award":["5600119"],"award-info":[{"award-number":["5600119"]}],"id":[{"id":"https:\/\/ror.org\/04s9fyw02","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Mol. Sci.","IJMS"],"abstract":"<jats:p>Bovine mastitis caused by Escherichia coli remains one of the most economically significant diseases in the dairy industry. This study performed a multi-layer transcriptome analysis of publicly available microarray data (GSE15025) derived from 15 German Holstein-Friesian heifers experimentally inoculated with E. coli, yielding 30 microarray samples across three GEO datasets (GSE15019, GSE15020, GSE15022) representing infected quarters at 6 h and 24 h post-inoculation and neighboring uninfected quarters at 24 h. Using an analytical framework combining WGCNA, differential gene expression profiling, PPI network construction, SVM classification, and computational miRNA target prediction, three significant co-expression modules were identified blue (367 genes, 6 h), turquoise (3602 genes, 24 h), and yellow (193 genes, 24 h neighboring tissue) alongside 21, 1570, and 250 differentially expressed genes respectively. Cross-referencing WGCNA and PPI analyses identified STAT3, JUN, and RAC2 as high-confidence hub gene candidates with the strongest convergent computational support. An SVM classifier achieved 87.5% accuracy (sensitivity = 100%, specificity = 75%) in distinguishing infected from control samples. Computational miRNA predictions suggested putative regulatory interactions requiring experimental confirmation. As a purely computational study, experimental validation remains a necessary future step; however, these findings provide a systematic characterization of candidate molecular mechanisms and potential biomarker targets for E. coli-induced bovine mastitis.<\/jats:p>","DOI":"10.3390\/ijms27167134","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T09:24:53Z","timestamp":1786353893000},"page":"7134","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-Layer Transcriptome Analysis Uncovers Molecular Signatures of Coliform Mastitis in Lactating Cows"],"prefix":"10.3390","volume":"27","author":[{"given":"Yamini Sri","family":"Sekar","sequence":"first","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kuralayanapalya Puttahonnappa","family":"Suresh","sequence":"additional","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3311-5886","authenticated-orcid":false,"given":"Shivasharanappa","family":"Nayakvadi","sequence":"additional","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0869-7722","authenticated-orcid":false,"given":"Bramhadev","family":"Pattnaik","sequence":"additional","affiliation":[{"name":"Institute of Veterinary Science and Animal Husbandry (IVSAH), Siksha O Anusandhan (SOA) University, Bhubaneswar 751029, OdishaIndia, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7108-6767","authenticated-orcid":false,"given":"Azhahianambi","family":"Palavesam","sequence":"additional","affiliation":[{"name":"Translational Research Platform for Veterinary Biologicals Centre for Animal Health Studies, Tamil Nadu Veterinary and Animal Sciences University, Chennai 600051, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9747-3426","authenticated-orcid":false,"given":"Nagendra Nath","family":"Barman","sequence":"additional","affiliation":[{"name":"Department of Veterinary Microbiology, College of Veterinary Science, Assam Agricultural University, Guwahati 785013, Assam, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hariprasad","family":"Thippeswamy","sequence":"additional","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Varsha","family":"Ramesh","sequence":"additional","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharanagouda Shiddanagouda","family":"Patil","sequence":"additional","affiliation":[{"name":"Indian Council of Agriculture Research (ICAR)-National Institute of Veterinary Epidemiology & Disease Informatics (NIVEDI), Bengaluru 560119, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1146\/annurev-resource-100518-093954","article-title":"Production Diseases Reduce the Efficiency of Dairy Production: A Review of the Results, Methods, and Approaches Regarding the Economics of Mastitis","volume":"11","author":"Hogeveen","year":"2019","journal-title":"Annu. Rev. Resour. Econ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"155","DOI":"10.2147\/IDR.S384776","article-title":"Is AMR in Dairy Products a Threat to Human Health? An Updated Review on the Origin, Prevention, Treatment, and Economic Impacts of Subclinical Mastitis","volume":"16","author":"Paramasivam","year":"2023","journal-title":"Infect. Drug Resist."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Tommasoni, C., Fiore, E., Lisuzzo, A., and Gianesella, M. (2023). Mastitis in Dairy Cattle: On-Farm Diagnostics and Future Perspectives. Animals, 13.","DOI":"10.3390\/ani13152538"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Haider, A., Ikram, M., Shahzadi, I., and Asif Raza, M. (2023). Polymeric Nanoparticles for Bovine Mastitis Treatment, Springer Nature.","DOI":"10.1007\/978-3-031-39947-3"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Kabelitz, T., Aubry, E., van Vorst, K., Amon, T., and Fulde, M. (2021). The Role of Streptococcus spp. in Bovine Mastitis. Microorganisms, 9.","DOI":"10.3390\/microorganisms9071497"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Shoaib, M., Aqib, A.I., Naseer, M.A., Bhutta, Z.A., Pu, W., Tanveer, Q., Muzammil, I., Kulyar, M.F.-E., Younas, M.S., and Hammad, M. (2022). Etiology of Bovine Mastitis. Mastitis in Dairy Cattle, Sheep and Goats, IntechOpen.","DOI":"10.5772\/intechopen.98543"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Cobirka, M., Tancin, V., and Slama, P. (2020). Epidemiology and Classification of Mastitis. Animals, 10.","DOI":"10.3390\/ani10122212"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Hoque, M.N., Istiaq, A., Clement, R.A., Sultana, M., Crandall, K.A., Siddiki, A.Z., and Hossain, M.A. (2019). Metagenomic deep sequencing reveals association of microbiome signature with functional biases in bovine mastitis. Sci. Rep., 9.","DOI":"10.1038\/s41598-019-49468-4"},{"key":"ref_9","unstructured":"Aavash, K., Sajita, G., Narayan, G.C., and Kumar, S.A. (2023). Prevalence of Subclinical Mastitis and Antibiogram of Escherichia coli in Cow Milk of Western Chitwan. J. Vet. Med. Res., 10."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Blum, S.E., Heller, E.D., Sela, S., Elad, D., Edery, N., and Leitner, G. (2015). Genomic and Phenomic Study of Mammary Pathogenic Escherichia coli. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0136387"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tong, X., Barkema, H.W., Nobrega, D.B., Xu, C., Han, B., Zhang, C., Yang, J., Li, X., and Gao, J. (2025). Virulence of Bacteria Causing Mastitis in Dairy Cows: A Literature Review. Microorganisms, 13.","DOI":"10.3390\/microorganisms13010167"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ghahramani, N., Shodja, J., Rafat, S.A., Panahi, B., and Hasanpur, K. (2021). Integrative Systems Biology Analysis Elucidates Mastitis Disease Underlying Functional Modules in Dairy Cattle. Front. Genet., 12.","DOI":"10.3389\/fgene.2021.712306"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Younis, S., Javed, Q., and Blumenberg, M. (2016). Meta-Analysis of Transcriptional Responses to Mastitis-Causing Escherichia coli. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0148562"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"309","DOI":"10.3390\/cimb44010023","article-title":"Multi-Omics Integration and Network Analysis Reveal Potential Hub Genes and Genetic Mechanisms Regulating Bovine Mastitis","volume":"44","author":"Naserkheil","year":"2022","journal-title":"Curr. Issues Mol. Biol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bakhtiarizadeh, M.R., Mirzaei, S., Norouzi, M., Sheybani, N., and Vafaei Sadi, M.S. (2020). Identification of Gene Modules and Hub Genes Involved in Mastitis Development Using a Systems Biology Approach. Front. Genet., 11.","DOI":"10.3389\/fgene.2020.00722"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wang, X., Xiu, L., Hu, Q., Cui, X., Liu, B., Tao, L., Wang, T., Wu, J., and Chen, Y. (2013). Deep Sequencing-Based Transcriptional Analysis of Bovine Mammary Epithelial Cells Gene Expression in Response to In Vitro Infection with Staphylococcus aureus Stains. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0082117"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Hasankhani, A., Bakherad, M., Bahrami, A., Shahrbabak, H.M., Pecho, R.D.C., and Shahrbabak, M.M. (2023). Integrated analysis of inflammatory mRNAs, miRNAs, and lncRNAs elucidates the molecular interactome behind bovine mastitis. Sci. Rep., 13, Correction in Sci. Rep. 2024, 14, 13778. https:\/\/doi.org\/10.1038\/s41598-024-64764-4.","DOI":"10.1038\/s41598-024-64764-4"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Goulart, D.B., and Mellata, M. (2022). Escherichia coli Mastitis in Dairy Cattle: Etiology, Diagnosis, and Treatment Challenges. Front. Microbiol., 13.","DOI":"10.3389\/fmicb.2022.928346"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Khan, M.Z., Khan, A., Xiao, J., Ma, J., Ma, Y., Chen, T., Shao, D., and Cao, Z. (2020). Overview of Research Development on the Role of NF-\u03baB Signaling in Mastitis. Animals, 10.","DOI":"10.3390\/ani10091625"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Dorrington, M.G., and Fraser, I.D.C. (2019). NF-\u03baB Signaling in Macrophages: Dynamics, Crosstalk, and Signal Integration. Front. Immunol., 10.","DOI":"10.3389\/fimmu.2019.00705"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"11167","DOI":"10.1021\/acs.jafc.9b04883","article-title":"MiR-16a Regulates Milk Fat Metabolism by Targeting Large Tumor Suppressor Kinase 1 (LATS1) in Bovine Mammary Epithelial Cells","volume":"67","author":"Chen","year":"2019","journal-title":"J. Agric. Food Chem."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhou, C., Li, C., Cai, W., Liu, S., Yin, H., Shi, S., Zhang, Q., and Zhang, S. (2019). Genome-wide association study for milk protein composition traits in a Chinese Holstein population using a single-step approach. Front. Genet., 10.","DOI":"10.3389\/fgene.2019.00072"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Bi, Y., Ding, Y., Wu, J., Miao, Z., Wang, J., and Wang, F. (2020). Staphylococcus aureus induces mammary gland fibrosis through activating the TLR\/NF-\u03baB and TLR\/AP-1 signaling pathways in mice. Microb. Pathog., 148.","DOI":"10.1016\/j.micpath.2020.104427"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Khan, M.Z., Khan, A., Xiao, J., Ma, Y., Ma, J., Gao, J., and Cao, Z. (2020). Role of the JAK-STAT Pathway in Bovine Mastitis and Milk Production. Animals, 10.","DOI":"10.3390\/ani10112107"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1007\/s11626-025-01055-w","article-title":"Lactiplantibacillus plantarum promotes lactoferrin synthesis and secretion in bovine mammary epithelial cells through STAT3 and AP-1 transcription factor pathways","volume":"61","author":"Zhou","year":"2025","journal-title":"Vitr. Cell. Dev. Biol. Anim."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"85","DOI":"10.4137\/BBI.S5850","article-title":"Expression of Metabolic, Tissue Remodeling, Oxidative Stress, and Inflammatory Pathways in Mammary Tissue during Involution in Lactating Dairy Cows","volume":"4","author":"Piantoni","year":"2010","journal-title":"Bioinform. Biol. Insights"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Alhussien, M.N., Panda, B.S.K., and Dang, A.K. (2021). A Comparative Study on Changes in Total and Differential Milk Cell Counts, Activity, and Expression of Milk Phagocytes of Healthy and Mastitic Indigenous Sahiwal Cows. Front. Vet. Sci., 8.","DOI":"10.3389\/fvets.2021.670811"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Gonen, E., Nedvetzki, S., Naor, D., and Shpigel, N.Y. (2008). CD44 is highly expressed on milk neutrophils in bovine mastitis and plays a role in their adhesion to matrix and mammary epithelium. Vet. Res., 39.","DOI":"10.1051\/vetres:2008005"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Liapi, M., Botsaris, G., Arsenoglou, C., Markantonis, N., Michael, C., Antoniou, A., and Pipis, C. (2021). Rapid Detection of Mycoplasma bovis, Staphylococcus aureus and Streptococcus agalactiae in Cattle Bulk Tank Milk in Cyprus and Relations with Somatic Cell Counts. Pathogens, 10.","DOI":"10.3390\/pathogens10070841"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"689","DOI":"10.2460\/ajvr.73.5.689","article-title":"Matrix metalloproteinase-9 expression in mammary gland tumors in dogs and its relationship with prognostic factors and patient outcome","volume":"73","author":"Santos","year":"2012","journal-title":"Am. J. Vet. Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Chattopadhyay, M., Jenkins, E.C., Janssen, W., Mashaka, T., and Germain, D. (2025). Differential ER stress responses during lactation and postpartum outcomes in mice depending on their mitochondrial genotype. Nat. Commun., 16.","DOI":"10.1038\/s41467-025-61666-5"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Yao, Y., Yang, J., Jiang, H., Meng, Y., Cao, W., Zhou, F., Wang, K., Yang, Z., and Yang, C. (2023). Assessment of adaptive immune responses of dairy cows with Burkholderia contaminans-induced mastitis. Front. Microbiol., 14.","DOI":"10.3389\/fmicb.2023.1099623"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1007\/s13353-019-00499-7","article-title":"Prediction of key regulators and downstream targets of E. coli induced mastitis","volume":"60","author":"Sharifi","year":"2019","journal-title":"J. Appl. Genet."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zhang, R., Zhang, Y., Zhang, M., Su, H., Zhao, F., Wang, D., Cao, G., and Zhang, Y. (2025). Regulation of LPS-Induced Inflammatory Responses in Bovine Mammary Epithelial Cells via TLR4-Mediated NF-\u03baB and MAPK Signaling Pathways by Lactoferrin. Life, 15.","DOI":"10.3390\/life15010069"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Wu, J., Li, L., Sun, Y., Huang, S., Tang, J., Yu, P., and Wang, G. (2015). Altered Molecular Expression of the TLR4\/NF-\u03baB Signaling Pathway in Mammary Tissue of Chinese Holstein Cattle with Mastitis. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0118458"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Yan, S., Ju, X., Lao, J., Wen, Z., Yong, Y., Li, Y., and Li, Y. (2024). Overexpression of the Mas1 gene mitigated LPS-induced inflammatory injury in mammary epithelial cells by inhibiting the NF-\u03baB\/MAPKs signaling pathways. Front. Vet. Sci., 11.","DOI":"10.3389\/fvets.2024.1446366"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"de Lima, A.O., Koltes, J.E., Diniz, W.J.S., de Oliveira, P.S.N., Cesar, A.S.M., Tizioto, P.C., Afonso, J., de Souza, M.M., Petrini, J., and Rocha, M.I.P. (2020). Potential Biomarkers for Feed Efficiency-Related Traits in Nelore Cattle Identified by Co-expression Network and Integrative Genomics Analyses. Front. Genet., 11.","DOI":"10.3389\/fgene.2020.00189"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1141","DOI":"10.5713\/ab.23.0323","article-title":"The role of RNA epigenetic modification-related genes in the immune response of cattle to mastitis induced by Staphylococcus aureus","volume":"37","author":"Xing","year":"2024","journal-title":"Anim. Biosci."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Cao, Y., Hu, G., Li, W., Wang, J., Ge, Y., Li, F., Guo, W., Kan, X., Fu, S., and Liu, J. (2022). Lysine promotes proliferation and \u03b2-casein synthesis through the SLC6A14-ERK1\/2-CDK1-mTOR signaling pathway in bovine primary mammary epithelial cells. J. Therm. Biol., 110.","DOI":"10.1016\/j.jtherbio.2022.103375"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Essa, B., Al-Sharif, M., Abdo, M., Fericean, L., and Ateya, A. (2023). New Insights on Nucleotide Sequence Variants and mRNA Levels of Candidate Genes Assessing Resistance\/Susceptibility to Mastitis in Holstein and Montb\u00e9liarde Dairy Cows. Vet. Sci., 10.","DOI":"10.3390\/vetsci10010035"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1006\/bbrc.2001.4780","article-title":"Expression of p40\/Epstein\u2013Barr Virus Nuclear Antigen 1 Binding Protein 2","volume":"283","author":"Henning","year":"2001","journal-title":"Biochem. Biophys. Res. Commun."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Lee, L., and Whittall, J.B. (2025). WDR75: An essential protein for ribosome assembly undergoing purifying selection. PLoS ONE, 20.","DOI":"10.1371\/journal.pone.0318395"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3423","DOI":"10.3168\/jds.S0022-0302(03)73946-0","article-title":"The Housekeeping Genes GAPDH and Cyclophilin Are Regulated by Metabolic State in the Liver of Dairy Cows","volume":"86","author":"Rhoads","year":"2003","journal-title":"J. Dairy Sci."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1007\/s10528-022-10254-z","article-title":"Identification of Key Genes and Potential Pathways Associated with Mastitis Induced by E. coli","volume":"61","author":"Darang","year":"2023","journal-title":"Biochem. Genet."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Morato, A., Martignani, E., Miretti, S., Baratta, M., and Accornero, P. (2021). External and internal EGFR-activating signals drive mammary epithelial cells proliferation and viability. Mol. Cell. Endocrinol., 520.","DOI":"10.1016\/j.mce.2020.111081"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"7645","DOI":"10.1128\/MCB.22.21.7645-7657.2002","article-title":"Rac2, a Hematopoiesis-Specific Rho GTPase, Specifically Regulates Mast Cell Protease Gene Expression in Bone Marrow-Derived Mast Cells","volume":"22","author":"Gu","year":"2002","journal-title":"Mol. Cell. Biol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/S1074-7613(00)80207-1","article-title":"Rac2 Stimulates Akt Activation Affecting BAD\/Bcl-XL Expression while Mediating Survival and Actin Function in Primary Mast Cells","volume":"12","author":"Yang","year":"2000","journal-title":"Immunity"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1084\/jem.194.7.915","article-title":"Deficiency of Small GTPase Rac2 Affects T Cell Activation","volume":"194","author":"Yu","year":"2001","journal-title":"J. Exp. Med."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Mitterhuemer, S., Petzl, W., Krebs, S., Mehne, D., Klanner, A., Wolf, E., Zerbe, H., and Blum, H. (2010). Escherichia coli infection induces distinct local and systemic transcriptome responses in the mammary gland. BMC Genom., 11.","DOI":"10.1186\/1471-2164-11-138"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Ritchie, M.E., Phipson, B., Wu, D., Hu, Y., Law, C.W., Shi, W., and Smyth, G.K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res., 43.","DOI":"10.1093\/nar\/gkv007"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Langfelder, P., and Horvath, S. (2008). WGCNA: An R package for weighted correlation network analysis. BMC Bioinform., 9.","DOI":"10.1186\/1471-2105-9-559"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Liao, Y., Wang, Y., Cheng, M., Huang, C., and Fan, X. (2020). Weighted Gene Coexpression Network Analysis of Features That Control Cancer Stem Cells Reveals Prognostic Biomarkers in Lung Adenocarcinoma. Front. Genet., 11.","DOI":"10.3389\/fgene.2020.00311"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Zhang, B., and Horvath, S. (2005). A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol., 4.","DOI":"10.2202\/1544-6115.1128"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1093\/bioinformatics\/btl633","article-title":"Enrichment or depletion of a GO category within a class of genes: Which test?","volume":"23","author":"Rivals","year":"2007","journal-title":"Bioinformatics"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Muley, V.Y. (2025). Functional Insights Through Gene Ontology, Disease Ontology, and KEGG Pathway Enrichment. Computational Virology, Springer.","DOI":"10.1007\/978-1-0716-4546-8_4"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"D607","DOI":"10.1093\/nar\/gky1131","article-title":"STRING v11: Protein\u2013protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets","volume":"47","author":"Szklarczyk","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1002\/0471250953.bi0813s47","article-title":"Biological Network Exploration with Cytoscape 3","volume":"47","author":"Su","year":"2014","journal-title":"Curr. Protoc. Bioinform."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Kalyan, G.U., Pranathi Reddy, D., Chandrakanth, G., Pooja, B., Anitha, V., and Vivek, D. (2023). Gene Association Disease Prediction by GEO2R Tool. 2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT), IEEE.","DOI":"10.1109\/EASCT59475.2023.10392802"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Song, Y.J., Li, G., He, J.H., Guo, Y., and Yang, L. (2015). Bioinformatics-Based Identification of MicroRNA-Regulated and Rheumatoid Arthritis-Associated Genes. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0137551"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Kontou, P.I., Pavlopoulou, A., and Bagos, P.G. (2018). Methods of Analysis and Meta-Analysis for Identifying Differentially Expressed Genes. Genetic Epidemiology: Methods and Protocols, Springer.","DOI":"10.1007\/978-1-4939-7868-7_12"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2621","DOI":"10.21037\/jtd-22-632","article-title":"Identification of hub genes and their correlation with immune infiltration in coronary artery disease through bioinformatics and machine learning methods","volume":"14","author":"Huang","year":"2022","journal-title":"J. Thorac. Dis."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building Predictive Models in R Using the caret Package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"James, G., Witten, D., Hastie, T., and Tibshirani, R. (2021). An Introduction to Statistical Learning, Springer.","DOI":"10.1007\/978-1-0716-1418-1"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1023\/A:1012487302797","article-title":"Gene Selection for Cancer Classification using Support Vector Machines","volume":"46","author":"Guyon","year":"2002","journal-title":"Mach. Learn."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"W244","DOI":"10.1093\/nar\/gkaa467","article-title":"miRNet 2.0: Network-based visual analytics for miRNA functional analysis and systems biology","volume":"48","author":"Chang","year":"2020","journal-title":"Nucleic Acids Res."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/16\/7134\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T09:33:56Z","timestamp":1786354436000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/16\/7134"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,9]]},"references-count":66,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["ijms27167134"],"URL":"https:\/\/doi.org\/10.3390\/ijms27167134","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,9]]}}}