These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
195 related articles for article (PubMed ID: 37884883)
1. Leveraging a disulfidptosis-related signature to predict the prognosis and immunotherapy effectiveness of cutaneous melanoma based on machine learning. Zhao Y; Wei Y; Fan L; Nie Y; Li J; Zeng R; Li J; Zhan X; Lei L; Kang Z; Li J; Zhang W; Yang Z Mol Med; 2023 Oct; 29(1):145. PubMed ID: 37884883 [TBL] [Abstract][Full Text] [Related]
2. Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients. Cheng S; Wang X; Yang S; Liang J; Song C; Zhu Q; Chen W; Ren Z; Zhu F Skin Res Technol; 2024 Jul; 30(7):e13814. PubMed ID: 38924611 [TBL] [Abstract][Full Text] [Related]
3. Bioinformatics-based analysis of the relationship between disulfidptosis and prognosis and treatment response in pancreatic cancer. Xiong Y; Kong X; Mei H; Wang J; Zhou S Sci Rep; 2023 Dec; 13(1):22218. PubMed ID: 38097783 [TBL] [Abstract][Full Text] [Related]
4. Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning. Xiao L; He R; Hu K; Song G; Han S; Lin J; Chen Y; Zhang D; Wang W; Peng Y; Zhang J; Yu P Apoptosis; 2024 Aug; 29(7-8):1070-1089. PubMed ID: 38615305 [TBL] [Abstract][Full Text] [Related]
5. Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma. Deng Z; Liu J; Yu YV; Jin YN Front Immunol; 2024; 15():1451103. PubMed ID: 39355255 [TBL] [Abstract][Full Text] [Related]
6. Leveraging a disulfidptosis-based signature to improve the survival and drug sensitivity of bladder cancer patients. Chen H; Yang W; Li Y; Ma L; Ji Z Front Immunol; 2023; 14():1198878. PubMed ID: 37325625 [TBL] [Abstract][Full Text] [Related]
7. Machine learning-based signature of necrosis-associated lncRNAs for prognostic and immunotherapy response prediction in cutaneous melanoma and tumor immune landscape characterization. Cui Z; Liang Z; Song B; Zhu Y; Chen G; Gu Y; Liang B; Ma J; Song B Front Endocrinol (Lausanne); 2023; 14():1180732. PubMed ID: 37229449 [TBL] [Abstract][Full Text] [Related]
8. Leveraging a gene signature associated with disulfidptosis identified by machine learning to forecast clinical outcomes, immunological heterogeneities, and potential therapeutic targets within lower-grade glioma. Zhou Y; Cao Y; Liu W; Wang L; Kuang Y; Zhou Y; Chen Q; Cheng Z; Huang H; Zhang W; Jiang X; Wang B; Ren C Front Immunol; 2023; 14():1294459. PubMed ID: 38162649 [TBL] [Abstract][Full Text] [Related]
9. Crosstalk of disulfidptosis-related subtypes, establishment of a prognostic signature and immune infiltration characteristics in bladder cancer based on a machine learning survival framework. Zhao S; Wang L; Ding W; Ye B; Cheng C; Shao J; Liu J; Zhou H Front Endocrinol (Lausanne); 2023; 14():1180404. PubMed ID: 37152941 [TBL] [Abstract][Full Text] [Related]
10. Identification of fatty acid metabolism-related molecular subtype biomarkers and their correlation with immune checkpoints in cutaneous melanoma. Xu Y; Chen Y; Jiang W; Yin X; Chen D; Chi Y; Wang Y; Zhang J; Zhang Q; Han Y Front Immunol; 2022; 13():967277. PubMed ID: 36466837 [TBL] [Abstract][Full Text] [Related]
11. Identification of disulfidptosis-related subtypes, characterization of tumor microenvironment infiltration, and development of a prognosis model in breast cancer. Liang J; Wang X; Yang J; Sun P; Sun J; Cheng S; Liu J; Ren Z; Ren M Front Immunol; 2023; 14():1198826. PubMed ID: 38035071 [TBL] [Abstract][Full Text] [Related]
12. Development and validation of an immune gene set-based prognostic signature in cutaneous melanoma. Tian Q; Gao H; Zhao W; Zhou Y; Yang J Future Oncol; 2021 Nov; 17(31):4115-4129. PubMed ID: 34291650 [TBL] [Abstract][Full Text] [Related]
13. A novel disulfidptosis-associated expression pattern in breast cancer based on machine learning. Wang Z; Du X; Lian W; Chen J; Hong C; Li L; Chen D Front Genet; 2023; 14():1193944. PubMed ID: 37456667 [No Abstract] [Full Text] [Related]
14. Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma. Zhu Z; Li G; Li Z; Wu Y; Yang Y; Wang M; Zhang H; Qu H; Song Z; He Y Front Immunol; 2022; 13():914612. PubMed ID: 36072600 [TBL] [Abstract][Full Text] [Related]
15. Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms. Chi H; Huang J; Yan Y; Jiang C; Zhang S; Chen H; Jiang L; Zhang J; Zhang Q; Yang G; Tian G Front Mol Biosci; 2023; 10():1254232. PubMed ID: 37916187 [No Abstract] [Full Text] [Related]
16. Clarifying new molecular subtyping and precise treatment of melanoma based on disulfidptosis-related lncRNA signature. Lei Y; Wang L; Liu P; Song Y; Gong Y; Jiang Y; Li S Eur J Med Res; 2024 Sep; 29(1):468. PubMed ID: 39342368 [TBL] [Abstract][Full Text] [Related]
17. Prediction of survival and immunotherapy response by the combined classifier of G protein-coupled receptors and tumor microenvironment in melanoma. Shen K; Wang Q; Wang L; Yang Y; Ren M; Li Y; Gao Z; Zheng S; Ding Y; Ji J; Wei C; Zhang T; Zhu Y; Feng J; Qin F; Yang Y; Wei C; Gu J Eur J Med Res; 2023 Sep; 28(1):352. PubMed ID: 37716991 [TBL] [Abstract][Full Text] [Related]
18. Single-cell sequencing and bulk RNA data reveal the tumor microenvironment infiltration characteristics of disulfidptosis related genes in breast cancer. Chen Y; Jin C; Cui J; Diao Y; Wang R; Xu R; Yao Z; Wu W; Li X J Cancer Res Clin Oncol; 2023 Oct; 149(13):12145-12164. PubMed ID: 37428249 [TBL] [Abstract][Full Text] [Related]
19. The development and experimental validation of hypoxia-related long noncoding RNAs prognostic signature in predicting prognosis and immunotherapy of cutaneous melanoma. Wang G; Sun Y; Xu Q Aging (Albany NY); 2023 Nov; 15(21):11918-11939. PubMed ID: 37921852 [TBL] [Abstract][Full Text] [Related]
20. Single-cell sequencing analysis related to sphingolipid metabolism guides immunotherapy and prognosis of skin cutaneous melanoma. Ding Y; Zhao Z; Cai H; Zhou Y; Chen H; Bai Y; Liu Z; Liu S; Zhou W Front Immunol; 2023; 14():1304466. PubMed ID: 38077400 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]