BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 29720995)

  • 1. Transcriptome-Wide Annotation of m
    Song J; Zhai J; Bian E; Song Y; Yu J; Ma C
    Front Plant Sci; 2018; 9():519. PubMed ID: 29720995
    [TBL] [Abstract][Full Text] [Related]  

  • 2. PEA: an integrated R toolkit for plant epitranscriptome analysis.
    Zhai J; Song J; Cheng Q; Tang Y; Ma C
    Bioinformatics; 2018 Nov; 34(21):3747-3749. PubMed ID: 29850798
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of m5C Modifications in RNA Sequences by Combining Multiple Sequence Features.
    Dou L; Li X; Ding H; Xu L; Xiang H
    Mol Ther Nucleic Acids; 2020 Sep; 21():332-342. PubMed ID: 32645685
    [TBL] [Abstract][Full Text] [Related]  

  • 4. im5C-DSCGA: A Proposed Hybrid Framework Based on Improved DenseNet and Attention Mechanisms for Identifying 5-methylcytosine Sites in Human RNA.
    Jia J; Qin L; Lei R
    Front Biosci (Landmark Ed); 2023 Dec; 28(12):346. PubMed ID: 38179749
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Staem5: A novel computational approachfor accurate prediction of m5C site.
    Chai D; Jia C; Zheng J; Zou Q; Li F
    Mol Ther Nucleic Acids; 2021 Dec; 26():1027-1034. PubMed ID: 34786208
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Episo: quantitative estimation of RNA 5-methylcytosine at isoform level by high-throughput sequencing of RNA treated with bisulfite.
    Liu J; An Z; Luo J; Li J; Li F; Zhang Z
    Bioinformatics; 2020 Apr; 36(7):2033-2039. PubMed ID: 31794005
    [TBL] [Abstract][Full Text] [Related]  

  • 7. m5C-Atlas: a comprehensive database for decoding and annotating the 5-methylcytosine (m5C) epitranscriptome.
    Ma J; Song B; Wei Z; Huang D; Zhang Y; Su J; de Magalhães JP; Rigden DJ; Meng J; Chen K
    Nucleic Acids Res; 2022 Jan; 50(D1):D196-D203. PubMed ID: 34986603
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble.
    Zhang M; Xu Y; Li L; Liu Z; Yang X; Yu DJ
    Anal Biochem; 2018 Jun; 550():41-48. PubMed ID: 29649472
    [TBL] [Abstract][Full Text] [Related]  

  • 9. m5CRegpred: Epitranscriptome Target Prediction of 5-Methylcytosine (m5C) Regulators Based on Sequencing Features.
    He Z; Xu J; Shi H; Wu S
    Genes (Basel); 2022 Apr; 13(4):. PubMed ID: 35456483
    [TBL] [Abstract][Full Text] [Related]  

  • 10. RNAm5CPred: Prediction of RNA 5-Methylcytosine Sites Based on Three Different Kinds of Nucleotide Composition.
    Fang T; Zhang Z; Sun R; Zhu L; He J; Huang B; Xiong Y; Zhu X
    Mol Ther Nucleic Acids; 2019 Dec; 18():739-747. PubMed ID: 31726390
    [TBL] [Abstract][Full Text] [Related]  

  • 11. m5CPred-SVM: a novel method for predicting m5C sites of RNA.
    Chen X; Xiong Y; Liu Y; Chen Y; Bi S; Zhu X
    BMC Bioinformatics; 2020 Oct; 21(1):489. PubMed ID: 33126851
    [TBL] [Abstract][Full Text] [Related]  

  • 12. iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition.
    Qiu WR; Jiang SY; Xu ZC; Xiao X; Chou KC
    Oncotarget; 2017 Jun; 8(25):41178-41188. PubMed ID: 28476023
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An improved residual network using deep fusion for identifying RNA 5-methylcytosine sites.
    Li X; Zhang S; Shi H
    Bioinformatics; 2022 Sep; 38(18):4271-4277. PubMed ID: 35866985
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Distinct 5-methylcytosine profiles in poly(A) RNA from mouse embryonic stem cells and brain.
    Amort T; Rieder D; Wille A; Khokhlova-Cubberley D; Riml C; Trixl L; Jia XY; Micura R; Lusser A
    Genome Biol; 2017 Jan; 18(1):1. PubMed ID: 28077169
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deciphering the epitranscriptome: A green perspective.
    Burgess A; David R; Searle IR
    J Integr Plant Biol; 2016 Oct; 58(10):822-835. PubMed ID: 27172004
    [TBL] [Abstract][Full Text] [Related]  

  • 16. MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.
    Kurata H; Harun-Or-Roshid M; Mehedi Hasan M; Tsukiyama S; Maeda K; Manavalan B
    Methods; 2024 Jul; 227():37-47. PubMed ID: 38729455
    [TBL] [Abstract][Full Text] [Related]  

  • 17. RNAm5Cfinder: A Web-server for Predicting RNA 5-methylcytosine (m5C) Sites Based on Random Forest.
    Li J; Huang Y; Yang X; Zhou Y; Zhou Y
    Sci Rep; 2018 Nov; 8(1):17299. PubMed ID: 30470762
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Transcriptome-Wide Mapping 5-Methylcytosine by m
    Gu X; Liang Z
    Methods Mol Biol; 2019; 1933():389-394. PubMed ID: 30945199
    [TBL] [Abstract][Full Text] [Related]  

  • 19. WHISTLE: A Functionally Annotated High-Accuracy Map of Human m
    Xu Q; Chen K; Meng J
    Methods Mol Biol; 2021; 2284():519-529. PubMed ID: 33835461
    [TBL] [Abstract][Full Text] [Related]  

  • 20. PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.
    Song M; Zhao J; Zhang C; Jia C; Yang J; Zhao H; Zhai J; Lei B; Tao S; Chen S; Su R; Ma C
    Plant Physiol; 2024 May; 195(2):1200-1213. PubMed ID: 38428981
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.