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 *

126 related articles for article (PubMed ID: 37356906)

  • 1. ISPRED-SEQ: Deep Neural Networks and Embeddings for Predicting Interaction Sites in Protein Sequences.
    Manfredi M; Savojardo C; Martelli PL; Casadio R
    J Mol Biol; 2023 Jul; 435(14):167963. PubMed ID: 37356906
    [TBL] [Abstract][Full Text] [Related]  

  • 2. CoCoNat: a novel method based on deep learning for coiled-coil prediction.
    Madeo G; Savojardo C; Manfredi M; Martelli PL; Casadio R
    Bioinformatics; 2023 Aug; 39(8):. PubMed ID: 37540220
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.
    Wu J; Liu B; Zhang J; Wang Z; Li J
    BMC Bioinformatics; 2023 Dec; 24(1):473. PubMed ID: 38097937
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Hierarchical graph learning for protein-protein interaction.
    Gao Z; Jiang C; Zhang J; Jiang X; Li L; Zhao P; Yang H; Huang Y; Li J
    Nat Commun; 2023 Feb; 14(1):1093. PubMed ID: 36841846
    [TBL] [Abstract][Full Text] [Related]  

  • 6. TUnA: an uncertainty-aware transformer model for sequence-based protein-protein interaction prediction.
    Ko YS; Parkinson J; Liu C; Wang W
    Brief Bioinform; 2024 Jul; 25(5):. PubMed ID: 39051117
    [TBL] [Abstract][Full Text] [Related]  

  • 7. GPSFun: geometry-aware protein sequence function predictions with language models.
    Yuan Q; Tian C; Song Y; Ou P; Zhu M; Zhao H; Yang Y
    Nucleic Acids Res; 2024 Jul; 52(W1):W248-W255. PubMed ID: 38738636
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Amino acid encoding for deep learning applications.
    ElAbd H; Bromberg Y; Hoarfrost A; Lenz T; Franke A; Wendorff M
    BMC Bioinformatics; 2020 Jun; 21(1):235. PubMed ID: 32517697
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predicting protein-protein interactions through sequence-based deep learning.
    Hashemifar S; Neyshabur B; Khan AA; Xu J
    Bioinformatics; 2018 Sep; 34(17):i802-i810. PubMed ID: 30423091
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Compound-protein interaction prediction with end-to-end learning of neural networks for graphs and sequences.
    Tsubaki M; Tomii K; Sese J
    Bioinformatics; 2019 Jan; 35(2):309-318. PubMed ID: 29982330
    [TBL] [Abstract][Full Text] [Related]  

  • 11. xCAPT5: protein-protein interaction prediction using deep and wide multi-kernel pooling convolutional neural networks with protein language model.
    Dang TH; Vu TA
    BMC Bioinformatics; 2024 Mar; 25(1):106. PubMed ID: 38461247
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep Neural Network Based Predictions of Protein Interactions Using Primary Sequences.
    Li H; Gong XJ; Yu H; Zhou C
    Molecules; 2018 Aug; 23(8):. PubMed ID: 30071670
    [TBL] [Abstract][Full Text] [Related]  

  • 13. E-SNPs&GO: embedding of protein sequence and function improves the annotation of human pathogenic variants.
    Manfredi M; Savojardo C; Martelli PL; Casadio R
    Bioinformatics; 2022 Nov; 38(23):5168-5174. PubMed ID: 36227117
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Graph-based prediction of Protein-protein interactions with attributed signed graph embedding.
    Yang F; Fan K; Song D; Lin H
    BMC Bioinformatics; 2020 Jul; 21(1):323. PubMed ID: 32693790
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Graph embeddings on gene ontology annotations for protein-protein interaction prediction.
    Zhong X; Rajapakse JC
    BMC Bioinformatics; 2020 Dec; 21(Suppl 16):560. PubMed ID: 33323115
    [TBL] [Abstract][Full Text] [Related]  

  • 16. DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions.
    Zhang F; Song H; Zeng M; Li Y; Kurgan L; Li M
    Proteomics; 2019 Jun; 19(12):e1900019. PubMed ID: 30941889
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.
    Zhou Y; Myung Y; Rodrigues CHM; Ascher DB
    Nucleic Acids Res; 2024 Jul; 52(W1):W207-W214. PubMed ID: 38783112
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information.
    Zhang F; Song H; Zeng M; Wu FX; Li Y; Pan Y; Li M
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(6):2208-2217. PubMed ID: 31985440
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Protein-protein interaction prediction based on ordinal regression and recurrent convolutional neural networks.
    Xu W; Gao Y; Wang Y; Guan J
    BMC Bioinformatics; 2021 Oct; 22(Suppl 6):485. PubMed ID: 34625020
    [TBL] [Abstract][Full Text] [Related]  

  • 20. PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein-protein interaction information.
    Yang H; Wang M; Liu X; Zhao XM; Li A
    Bioinformatics; 2021 Dec; 37(24):4668-4676. PubMed ID: 34320631
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.