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 *

160 related articles for article (PubMed ID: 38058187)

  • 1. Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.
    Pham NT; Phan LT; Seo J; Kim Y; Song M; Lee S; Jeon YJ; Manavalan B
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38058187
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Adaptive learning embedding features to improve the predictive performance of SARS-CoV-2 phosphorylation sites.
    Jiao S; Ye X; Ao C; Sakurai T; Zou Q; Xu L
    Bioinformatics; 2023 Nov; 39(11):. PubMed ID: 37847658
    [TBL] [Abstract][Full Text] [Related]  

  • 3. DeepPPSite: A deep learning-based model for analysis and prediction of phosphorylation sites using efficient sequence information.
    Ahmed S; Kabir M; Arif M; Khan ZU; Yu DJ
    Anal Biochem; 2021 Jan; 612():113955. PubMed ID: 32949607
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeepSSPred: A Deep Learning Based Sulfenylation Site Predictor Via a Novel nSegmented Optimize Federated Feature Encoder.
    Khan ZU; Pi D
    Protein Pept Lett; 2021; 28(6):708-721. PubMed ID: 33267753
    [TBL] [Abstract][Full Text] [Related]  

  • 5. IPs-GRUAtt: An attention-based bidirectional gated recurrent unit network for predicting phosphorylation sites of SARS-CoV-2 infection.
    Zhang G; Tang Q; Feng P; Chen W
    Mol Ther Nucleic Acids; 2023 Jun; 32():28-35. PubMed ID: 36908648
    [TBL] [Abstract][Full Text] [Related]  

  • 6. DE-MHAIPs: Identification of SARS-CoV-2 phosphorylation sites based on differential evolution multi-feature learning and multi-head attention mechanism.
    Wang M; Yan L; Jia J; Lai J; Zhou H; Yu B
    Comput Biol Med; 2023 Jun; 160():106935. PubMed ID: 37120990
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Boosting phosphorylation site prediction with sequence feature-based machine learning.
    Maiti S; Hassan A; Mitra P
    Proteins; 2020 Feb; 88(2):284-291. PubMed ID: 31412138
    [TBL] [Abstract][Full Text] [Related]  

  • 8. ADP-Fuse: A novel two-layer machine learning predictor to identify antidiabetic peptides and diabetes types using multiview information.
    Basith S; Pham NT; Song M; Lee G; Manavalan B
    Comput Biol Med; 2023 Oct; 165():107386. PubMed ID: 37619323
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2.
    Manavalan B; Basith S; Lee G
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34595489
    [TBL] [Abstract][Full Text] [Related]  

  • 10. DeepIPs: comprehensive assessment and computational identification of phosphorylation sites of SARS-CoV-2 infection using a deep learning-based approach.
    Lv H; Dao FY; Zulfiqar H; Lin H
    Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34184738
    [TBL] [Abstract][Full Text] [Related]  

  • 11. COVID-Net Biochem: an explainability-driven framework to building machine learning models for predicting survival and kidney injury of COVID-19 patients from clinical and biochemistry data.
    Aboutalebi H; Pavlova M; Shafiee MJ; Florea A; Hryniowski A; Wong A
    Sci Rep; 2023 Oct; 13(1):17001. PubMed ID: 37813920
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Prediction of death status on the course of treatment in SARS-COV-2 patients with deep learning and machine learning methods.
    Kivrak M; Guldogan E; Colak C
    Comput Methods Programs Biomed; 2021 Apr; 201():105951. PubMed ID: 33513487
    [TBL] [Abstract][Full Text] [Related]  

  • 13. H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.
    Pham NT; Rakkiyapan R; Park J; Malik A; Manavalan B
    Brief Bioinform; 2023 Nov; 25(1):. PubMed ID: 38180830
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Predicting protein phosphorylation sites in soybean using interpretable deep tabular learning network.
    Khalili E; Ramazi S; Ghanati F; Kouchaki S
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35152280
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Accurately predicting microbial phosphorylation sites using evolutionary and structural features.
    Ahmed F; Dehzangi I; Hasan MM; Shatabda S
    Gene; 2023 Jan; 851():146993. PubMed ID: 36272653
    [TBL] [Abstract][Full Text] [Related]  

  • 16. ResNetKhib: a novel cell type-specific tool for predicting lysine 2-hydroxyisobutylation sites via transfer learning.
    Jia X; Zhao P; Li F; Qin Z; Ren H; Li J; Miao C; Zhao Q; Akutsu T; Dou G; Chen Z; Song J
    Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36880172
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers.
    Krishnamoorthy P; Raj AS; Kumar H
    J Med Virol; 2023 Feb; 95(2):e28488. PubMed ID: 36625381
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Clinical Features of Emergency Department Patients from Early COVID-19 Pandemic that Predict SARS-CoV-2 Infection: Machine-learning Approach.
    Chou EH; Wang CH; Hsieh YL; Namazi B; Wolfshohl J; Bhakta T; Tsai CL; Lien WC; Sankaranarayanan G; Lee CC; Lu TC
    West J Emerg Med; 2021 Mar; 22(2):244-251. PubMed ID: 33856307
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A prospective, randomized, single-blinded, crossover trial to investigate the effect of a wearable device in addition to a daily symptom diary for the Remote Early Detection of SARS-CoV-2 infections (COVID-RED): a structured summary of a study protocol for a randomized controlled trial.
    Brakenhoff TB; Franks B; Goodale BM; van de Wijgert J; Montes S; Veen D; Fredslund EK; Rispens T; Risch L; Dowling AV; Folarin AA; Bruijning P; Dobson R; Heikamp T; Klaver P; Cronin M; Grobbee DE;
    Trials; 2021 Oct; 22(1):694. PubMed ID: 34635140
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Variation in the ACE2 receptor has limited utility for SARS-CoV-2 host prediction.
    Mollentze N; Keen D; Munkhbayar U; Biek R; Streicker DG
    Elife; 2022 Nov; 11():. PubMed ID: 36416537
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.