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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

169 related articles for article (PubMed ID: 36381577)

  • 1. 4acCPred: Weakly supervised prediction of
    Zhou J; Wang X; Wei Z; Meng J; Huang D
    Mol Ther Nucleic Acids; 2022 Dec; 30():337-345. PubMed ID: 36381577
    [TBL] [Abstract][Full Text] [Related]  

  • 2. N
    Wang S; Xie H; Mao F; Wang H; Wang S; Chen Z; Zhang Y; Xu Z; Xing J; Cui Z; Gao X; Jin H; Hua J; Xiong B; Wu Y
    Genome Biol; 2022 Jan; 23(1):5. PubMed ID: 34980211
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data.
    Huang D; Song B; Wei J; Su J; Coenen F; Meng J
    Bioinformatics; 2021 Jul; 37(Suppl_1):i222-i230. PubMed ID: 34252943
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning.
    Xu H; Jia P; Zhao Z
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32578842
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comprehensive review and assessment of computational methods for predicting RNA post-transcriptional modification sites from RNA sequences.
    Chen Z; Zhao P; Li F; Wang Y; Smith AI; Webb GI; Akutsu T; Baggag A; Bensmail H; Song J
    Brief Bioinform; 2020 Sep; 21(5):1676-1696. PubMed ID: 31714956
    [TBL] [Abstract][Full Text] [Related]  

  • 6. m6A-Maize: Weakly supervised prediction of m
    Liang Z; Zhang L; Chen H; Huang D; Song B
    Methods; 2022 Jul; 203():226-232. PubMed ID: 34843978
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modeling in-vivo protein-DNA binding by combining multiple-instance learning with a hybrid deep neural network.
    Zhang Q; Shen Z; Huang DS
    Sci Rep; 2019 Jun; 9(1):8484. PubMed ID: 31186519
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
    Ghaffari Laleh N; Muti HS; Loeffler CML; Echle A; Saldanha OL; Mahmood F; Lu MY; Trautwein C; Langer R; Dislich B; Buelow RD; Grabsch HI; Brenner H; Chang-Claude J; Alwers E; Brinker TJ; Khader F; Truhn D; Gaisa NT; Boor P; Hoffmeister M; Schulz V; Kather JN
    Med Image Anal; 2022 Jul; 79():102474. PubMed ID: 35588568
    [TBL] [Abstract][Full Text] [Related]  

  • 9. CNNLSTMac4CPred: A Hybrid Model for N4-Acetylcytidine Prediction.
    Zhang G; Luo W; Lyu J; Yu ZG; Huang G
    Interdiscip Sci; 2022 Jun; 14(2):439-451. PubMed ID: 35106702
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Self-attention enabled deep learning of dihydrouridine (D) modification on mRNAs unveiled a distinct sequence signature from tRNAs.
    Wang Y; Wang X; Cui X; Meng J; Rong R
    Mol Ther Nucleic Acids; 2023 Mar; 31():411-420. PubMed ID: 36845339
    [TBL] [Abstract][Full Text] [Related]  

  • 11. UD-MIL: Uncertainty-Driven Deep Multiple Instance Learning for OCT Image Classification.
    Wang X; Tang F; Chen H; Luo L; Tang Z; Ran AR; Cheung CY; Heng PA
    IEEE J Biomed Health Inform; 2020 Dec; 24(12):3431-3442. PubMed ID: 32248132
    [TBL] [Abstract][Full Text] [Related]  

  • 12. iDNA-MT: Identification DNA Modification Sites in Multiple Species by Using Multi-Task Learning Based a Neural Network Tool.
    Yang X; Ye X; Li X; Wei L
    Front Genet; 2021; 12():663572. PubMed ID: 33868390
    [TBL] [Abstract][Full Text] [Related]  

  • 13. EMDLP: Ensemble multiscale deep learning model for RNA methylation site prediction.
    Wang H; Liu H; Huang T; Li G; Zhang L; Sun Y
    BMC Bioinformatics; 2022 Jun; 23(1):221. PubMed ID: 35676633
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Weakly Supervised Learning of 3D Deep Network for Neuron Reconstruction.
    Huang Q; Chen Y; Liu S; Xu C; Cao T; Xu Y; Wang X; Rao G; Li A; Zeng S; Quan T
    Front Neuroanat; 2020; 14():38. PubMed ID: 32848636
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Developing a Multi-Layer Deep Learning Based Predictive Model to Identify DNA N4-Methylcytosine Modifications.
    Zeng R; Liao M
    Front Bioeng Biotechnol; 2020; 8():274. PubMed ID: 32373597
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites.
    Liu Q; Chen J; Wang Y; Li S; Jia C; Song J; Li F
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32608476
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information.
    Liu ML; Su W; Wang JS; Yang YH; Yang H; Lin H
    Mol Ther Nucleic Acids; 2020 Dec; 22():1043-1050. PubMed ID: 33294291
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Identifying DNA N4-methylcytosine sites in the rosaceae genome with a deep learning model relying on distributed feature representation.
    Khanal J; Tayara H; Zou Q; Chong KT
    Comput Struct Biotechnol J; 2021; 19():1612-1619. PubMed ID: 33868598
    [TBL] [Abstract][Full Text] [Related]  

  • 19. RicENN: Prediction of Rice Enhancers with Neural Network Based on DNA Sequences.
    Gao Y; Chen Y; Feng H; Zhang Y; Yue Z
    Interdiscip Sci; 2022 Jun; 14(2):555-565. PubMed ID: 35190950
    [TBL] [Abstract][Full Text] [Related]  

  • 20. m5UPred: A Web Server for the Prediction of RNA 5-Methyluridine Sites from Sequences.
    Jiang J; Song B; Tang Y; Chen K; Wei Z; Meng J
    Mol Ther Nucleic Acids; 2020 Dec; 22():742-747. PubMed ID: 33230471
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.