BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

116 related articles for article (PubMed ID: 38070457)

  • 1. An ensemble of bioinformatics and machine learning approaches to identify shared breast cancer biomarkers among diverse populations.
    Sultan G; Zubair S
    Comput Biol Chem; 2024 Feb; 108():107999. PubMed ID: 38070457
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Identifying cancer biomarkers by network-constrained support vector machines.
    Chen L; Xuan J; Riggins RB; Clarke R; Wang Y
    BMC Syst Biol; 2011 Oct; 5():161. PubMed ID: 21992556
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning integrated ensemble of feature selection methods followed by survival analysis for predicting breast cancer subtype specific miRNA biomarkers.
    Sarkar JP; Saha I; Sarkar A; Maulik U
    Comput Biol Med; 2021 Apr; 131():104244. PubMed ID: 33550016
    [TBL] [Abstract][Full Text] [Related]  

  • 4. In silico analysis of differentially expressed genesets in metastatic breast cancer identifies potential prognostic biomarkers.
    Kim J
    World J Surg Oncol; 2021 Jun; 19(1):188. PubMed ID: 34172056
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Refining breast cancer biomarker discovery and drug targeting through an advanced data-driven approach.
    Rakhshaninejad M; Fathian M; Shirkoohi R; Barzinpour F; Gandomi AH
    BMC Bioinformatics; 2024 Jan; 25(1):33. PubMed ID: 38253993
    [TBL] [Abstract][Full Text] [Related]  

  • 6. RNA-Seq-Based Breast Cancer Subtypes Classification Using Machine Learning Approaches.
    Yu Z; Wang Z; Yu X; Zhang Z
    Comput Intell Neurosci; 2020; 2020():4737969. PubMed ID: 33178256
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Systems biology comprehensive analysis on breast cancer for identification of key gene modules and genes associated with TNM-based clinical stages.
    Amjad E; Asnaashari S; Sokouti B; Dastmalchi S
    Sci Rep; 2020 Jul; 10(1):10816. PubMed ID: 32616754
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tree-based machine learning algorithms identified minimal set of miRNA biomarkers for breast cancer diagnosis and molecular subtyping.
    Sherafatian M
    Gene; 2018 Nov; 677():111-118. PubMed ID: 30055304
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Identification of potential crucial genes and key pathways shared in Inflammatory Bowel Disease and cervical cancer by machine learning and integrated bioinformatics.
    Nguyen TB; Do DN; Nguyen-Thi ML; Hoang-The H; Tran TT; Nguyen-Thanh T
    Comput Biol Med; 2022 Oct; 149():105996. PubMed ID: 36049413
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer.
    Zhou Q; Ren J; Hou J; Wang G; Ju L; Xiao Y; Gong Y
    J Cancer Res Clin Oncol; 2019 Sep; 145(9):2383-2396. PubMed ID: 31280346
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.
    Zhang C; Peng L; Zhang Y; Liu Z; Li W; Chen S; Li G
    Med Oncol; 2017 Jun; 34(6):101. PubMed ID: 28432618
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.
    Li MX; Sun XM; Cheng WG; Ruan HJ; Liu K; Chen P; Xu HJ; Gao SG; Feng XS; Qi YJ
    BMC Cancer; 2021 Aug; 21(1):906. PubMed ID: 34372798
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An Integrated Systems Biology and Network-Based Approaches to Identify Novel Biomarkers in Breast Cancer Cell Lines Using Gene Expression Data.
    Khan A; Rehman Z; Hashmi HF; Khan AA; Junaid M; Sayaf AM; Ali SS; Hassan FU; Heng W; Wei DQ
    Interdiscip Sci; 2020 Jun; 12(2):155-168. PubMed ID: 32056139
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Integrated network analysis and machine learning approach for the identification of key genes of triple-negative breast cancer.
    Naorem LD; Muthaiyan M; Venkatesan A
    J Cell Biochem; 2019 Apr; 120(4):6154-6167. PubMed ID: 30302816
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Breast cancer stage prediction: a computational approach guided by transcriptome analysis.
    Athira K; Gopakumar G
    Mol Genet Genomics; 2022 Nov; 297(6):1467-1479. PubMed ID: 35922530
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Identification of differentially expressed genes regulated by molecular signature in breast cancer-associated fibroblasts by bioinformatics analysis.
    Vastrad B; Vastrad C; Tengli A; Iliger S
    Arch Gynecol Obstet; 2018 Jan; 297(1):161-183. PubMed ID: 29063236
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identification of Novel Biomarkers Associated With the Prognosis and Potential Pathogenesis of Breast Cancer via Integrated Bioinformatics Analysis.
    Wu M; Li Q; Wang H
    Technol Cancer Res Treat; 2021; 20():1533033821992081. PubMed ID: 33550915
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis.
    Chen G; Yu M; Cao J; Zhao H; Dai Y; Cong Y; Qiao G
    Bioengineered; 2021 Dec; 12(1):5149-5161. PubMed ID: 34384030
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A critical evaluation of network and pathway-based classifiers for outcome prediction in breast cancer.
    Staiger C; Cadot S; Kooter R; Dittrich M; Müller T; Klau GW; Wessels LF
    PLoS One; 2012; 7(4):e34796. PubMed ID: 22558100
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Key Genes and Prognostic Analysis in HER2+ Breast Cancer.
    Weng Y; Liang W; Ji Y; Li Z; Jia R; Liang Y; Ning P; Xu Y
    Technol Cancer Res Treat; 2021; 20():1533033820983298. PubMed ID: 33499770
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.