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 *

178 related articles for article (PubMed ID: 39196703)

  • 1. Structure-aware deep learning model for peptide toxicity prediction.
    Ebrahimikondori H; Sutherland D; Yanai A; Richter A; Salehi A; Li C; Coombe L; Kotkoff M; Warren RL; Birol I
    Protein Sci; 2024 Jul; 33(7):e5076. PubMed ID: 39196703
    [TBL] [Abstract][Full Text] [Related]  

  • 2. TP-LMMSG: a peptide prediction graph neural network incorporating flexible amino acid property representation.
    Chen N; Yu J; Zhe L; Wang F; Li X; Wong KC
    Brief Bioinform; 2024 May; 25(4):. PubMed ID: 38920345
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.
    Cordoves-Delgado G; García-Jacas CR
    J Chem Inf Model; 2024 May; 64(10):4310-4321. PubMed ID: 38739853
    [TBL] [Abstract][Full Text] [Related]  

  • 4. AMP-RNNpro: a two-stage approach for identification of antimicrobials using probabilistic features.
    Shaon MSH; Karim T; Sultan MF; Ali MM; Ahmed K; Hasan MZ; Moustafa A; Bui FM; Al-Zahrani FA
    Sci Rep; 2024 Jun; 14(1):12892. PubMed ID: 38839785
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.
    Du J; Yang C; Deng Y; Guo H; Gu M; Chen D; Liu X; Huang J; Yan W; Liu J
    Eur J Med Chem; 2024 Nov; 277():116797. PubMed ID: 39197254
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparison of deep learning models with simple method to assess the problem of antimicrobial peptides prediction.
    Lobanov MY; Slizen MV; Dovidchenko NV; Panfilov AV; Surin AA; Likhachev IV; Galzitskaya OV
    Mol Inform; 2024 May; 43(5):e202200181. PubMed ID: 36961202
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An efficient hybrid deep learning architecture for predicting short antimicrobial peptides.
    Nguyen QH; Nguyen-Vo TH; Do TTT; Nguyen BP
    Proteomics; 2024 Jul; 24(14):e2300382. PubMed ID: 38837544
    [TBL] [Abstract][Full Text] [Related]  

  • 8. De Novo Antimicrobial Peptide Design with Feedback Generative Adversarial Networks.
    Zervou MA; Doutsi E; Pantazis Y; Tsakalides P
    Int J Mol Sci; 2024 May; 25(10):. PubMed ID: 38791544
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A deep learning method for predicting the minimum inhibitory concentration of antimicrobial peptides against
    Yan J; Zhang B; Zhou M; Campbell-Valois FX; Siu SWI
    mSystems; 2023 Aug; 8(4):e0034523. PubMed ID: 37431995
    [TBL] [Abstract][Full Text] [Related]  

  • 10. AMP-BERT: Prediction of antimicrobial peptide function based on a BERT model.
    Lee H; Lee S; Lee I; Nam H
    Protein Sci; 2023 Jan; 32(1):e4529. PubMed ID: 36461699
    [TBL] [Abstract][Full Text] [Related]  

  • 11. EnAMP: A novel deep learning ensemble antibacterial peptide recognition algorithm based on multi-features.
    Zhuang J; Gao W; Su R
    J Bioinform Comput Biol; 2024 Feb; 22(1):2450001. PubMed ID: 38406833
    [TBL] [Abstract][Full Text] [Related]  

  • 12. deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model.
    Zhao F; Qiu J; Xiang D; Jiao P; Cao Y; Xu Q; Qiao D; Xu H; Cao Y
    PeerJ; 2024; 12():e17729. PubMed ID: 39040937
    [TBL] [Abstract][Full Text] [Related]  

  • 13. De novo synthetic antimicrobial peptide design with a recurrent neural network.
    Li C; Sutherland D; Richter A; Coombe L; Yanai A; Warren RL; Kotkoff M; Hof F; Hoang LMN; Helbing CC; Birol I
    Protein Sci; 2024 Aug; 33(8):e5088. PubMed ID: 38988311
    [TBL] [Abstract][Full Text] [Related]  

  • 14. AMPDeep: hemolytic activity prediction of antimicrobial peptides using transfer learning.
    Salem M; Keshavarzi Arshadi A; Yuan JS
    BMC Bioinformatics; 2022 Sep; 23(1):389. PubMed ID: 36163001
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep-learning-enabled antibiotic discovery through molecular de-extinction.
    Wan F; Torres MDT; Peng J; de la Fuente-Nunez C
    Nat Biomed Eng; 2024 Jul; 8(7):854-871. PubMed ID: 38862735
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Energy-based graph convolutional networks for scoring protein docking models.
    Cao Y; Shen Y
    Proteins; 2020 Aug; 88(8):1091-1099. PubMed ID: 32144844
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine Learning Prediction of Antimicrobial Peptides.
    Wang G; Vaisman II; van Hoek ML
    Methods Mol Biol; 2022; 2405():1-37. PubMed ID: 35298806
    [TBL] [Abstract][Full Text] [Related]  

  • 18. PGAT-ABPp: harnessing protein language models and graph attention networks for antibacterial peptide identification with remarkable accuracy.
    Hao Y; Liu X; Fu H; Shao X; Cai W
    Bioinformatics; 2024 Aug; 40(8):. PubMed ID: 39120878
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Do deep learning models make a difference in the identification of antimicrobial peptides?
    García-Jacas CR; Pinacho-Castellanos SA; García-González LA; Brizuela CA
    Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35380616
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Multimodal deep representation learning for protein interaction identification and protein family classification.
    Zhang D; Kabuka M
    BMC Bioinformatics; 2019 Dec; 20(Suppl 16):531. PubMed ID: 31787089
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.