Identification of Glycolysis-Related Signature and Molecular Subtypes in Child Sepsis Through Machine Learning and Consensus Clustering: Implications for Diagnosis and Therapeutics.
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| Title: | Identification of Glycolysis-Related Signature and Molecular Subtypes in Child Sepsis Through Machine Learning and Consensus Clustering: Implications for Diagnosis and Therapeutics. |
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| Authors: | Ma C; Department of Emergency, Third People's Hospital of Cixi, Zhejiang, Ningbo, China., Wang J; Xi'an International Medical Center Hospital, No.777, Xitai Road, High-tech Zone, Xi'an, 710000, Shaanxi, China. wangjl240003@163.com. |
| Source: | Molecular biotechnology [Mol Biotechnol] 2026 Feb; Vol. 68 (2), pp. 507-521. Date of Electronic Publication: 2025 Feb 20. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: Switzerland NLM ID: 9423533 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1559-0305 (Electronic) Linking ISSN: 10736085 NLM ISO Abbreviation: Mol Biotechnol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1559-0305 |
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| DOI: | 10.1007/s12033-025-01379-8 |
