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 *

223 related articles for article (PubMed ID: 31265154)

  • 1. Estimation of model accuracy in CASP13.
    Cheng J; Choe MH; Elofsson A; Han KS; Hou J; Maghrabi AHA; McGuffin LJ; Menéndez-Hurtado D; Olechnovič K; Schwede T; Studer G; Uziela K; Venclovas Č; Wallner B
    Proteins; 2019 Dec; 87(12):1361-1377. PubMed ID: 31265154
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Assessment of protein model structure accuracy estimation in CASP13: Challenges in the era of deep learning.
    Won J; Baek M; Monastyrskyy B; Kryshtafovych A; Seok C
    Proteins; 2019 Dec; 87(12):1351-1360. PubMed ID: 31436360
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Analysis of distance-based protein structure prediction by deep learning in CASP13.
    Xu J; Wang S
    Proteins; 2019 Dec; 87(12):1069-1081. PubMed ID: 31471916
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Methods for estimation of model accuracy in CASP12.
    Elofsson A; Joo K; Keasar C; Lee J; Maghrabi AHA; Manavalan B; McGuffin LJ; Ménendez Hurtado D; Mirabello C; Pilstål R; Sidi T; Uziela K; Wallner B
    Proteins; 2018 Mar; 86 Suppl 1():361-373. PubMed ID: 28975666
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments.
    Abriata LA; Tamò GE; Dal Peraro M
    Proteins; 2019 Dec; 87(12):1100-1112. PubMed ID: 31344267
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep-learning contact-map guided protein structure prediction in CASP13.
    Zheng W; Li Y; Zhang C; Pearce R; Mortuza SM; Zhang Y
    Proteins; 2019 Dec; 87(12):1149-1164. PubMed ID: 31365149
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13.
    Hou J; Wu T; Cao R; Cheng J
    Proteins; 2019 Dec; 87(12):1165-1178. PubMed ID: 30985027
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Small angle X-ray scattering-assisted protein structure prediction in CASP13 and emergence of solution structure differences.
    Hura GL; Hodge CD; Rosenberg D; Guzenko D; Duarte JM; Monastyrskyy B; Grudinin S; Kryshtafovych A; Tainer JA; Fidelis K; Tsutakawa SE
    Proteins; 2019 Dec; 87(12):1298-1314. PubMed ID: 31589784
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Assessment of model accuracy estimations in CASP12.
    Kryshtafovych A; Monastyrskyy B; Fidelis K; Schwede T; Tramontano A
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):345-360. PubMed ID: 28833563
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12.
    Zhang C; Mortuza SM; He B; Wang Y; Zhang Y
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):136-151. PubMed ID: 29082551
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13.
    Li Y; Zhang C; Bell EW; Yu DJ; Zhang Y
    Proteins; 2019 Dec; 87(12):1082-1091. PubMed ID: 31407406
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Evaluation of model refinement in CASP13.
    Read RJ; Sammito MD; Kryshtafovych A; Croll TI
    Proteins; 2019 Dec; 87(12):1249-1262. PubMed ID: 31365160
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Driven to near-experimental accuracy by refinement via molecular dynamics simulations.
    Heo L; Arbour CF; Feig M
    Proteins; 2019 Dec; 87(12):1263-1275. PubMed ID: 31197841
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Evaluation of template-based modeling in CASP13.
    Croll TI; Sammito MD; Kryshtafovych A; Read RJ
    Proteins; 2019 Dec; 87(12):1113-1127. PubMed ID: 31407380
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.
    Adhikari B; Hou J; Cheng J
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):84-96. PubMed ID: 29047157
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessing the accuracy of contact predictions in CASP13.
    Shrestha R; Fajardo E; Gil N; Fidelis K; Kryshtafovych A; Monastyrskyy B; Fiser A
    Proteins; 2019 Dec; 87(12):1058-1068. PubMed ID: 31587357
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Prediction of interresidue contacts with DeepMetaPSICOV in CASP13.
    Kandathil SM; Greener JG; Jones DT
    Proteins; 2019 Dec; 87(12):1092-1099. PubMed ID: 31298436
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Critical assessment of methods of protein structure prediction (CASP)-Round XIII.
    Kryshtafovych A; Schwede T; Topf M; Fidelis K; Moult J
    Proteins; 2019 Dec; 87(12):1011-1020. PubMed ID: 31589781
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Accurate template-based modeling in CASP12 using the IntFOLD4-TS, ModFOLD6, and ReFOLD methods.
    McGuffin LJ; Shuid AN; Kempster R; Maghrabi AHA; Nealon JO; Salehe BR; Atkins JD; Roche DB
    Proteins; 2018 Mar; 86 Suppl 1():335-344. PubMed ID: 28748648
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Assessment of protein assembly prediction in CASP12.
    Lafita A; Bliven S; Kryshtafovych A; Bertoni M; Monastyrskyy B; Duarte JM; Schwede T; Capitani G
    Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):247-256. PubMed ID: 29071742
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.