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 *

189 related articles for article (PubMed ID: 37079494)

  • 1. Bridging the gap between mechanistic biological models and machine learning surrogates.
    Gherman IM; Abdallah ZS; Pang W; Gorochowski TE; Grierson CS; Marucci L
    PLoS Comput Biol; 2023 Apr; 19(4):e1010988. PubMed ID: 37079494
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning Approaches to Surrogates for Solving the Diffusion Equation for Mechanistic Real-World Simulations.
    Toledo-Marín JQ; Fox G; Sluka JP; Glazier JA
    Front Physiol; 2021; 12():667828. PubMed ID: 34248661
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.
    Cuperlovic-Culf M; Nguyen-Tran T; Bennett SAL
    Methods Mol Biol; 2023; 2553():417-439. PubMed ID: 36227553
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Accelerating hydrodynamic simulations of urban drainage systems with physics-guided machine learning.
    Palmitessa R; Grum M; Engsig-Karup AP; Löwe R
    Water Res; 2022 Sep; 223():118972. PubMed ID: 35994785
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SysBioMed report: advancing systems biology for medical applications.
    Wolkenhauer O; Fell D; De Meyts P; Blüthgen N; Herzel H; Le Novère N; Höfer T; Schürrle K; van Leeuwen I
    IET Syst Biol; 2009 May; 3(3):131-6. PubMed ID: 19449974
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).
    Foffi G; Pastore A; Piazza F; Temussi PA
    Phys Biol; 2013 Aug; 10(4):040301. PubMed ID: 23912807
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Using machine learning as a surrogate model for agent-based simulations.
    Angione C; Silverman E; Yaneske E
    PLoS One; 2022; 17(2):e0263150. PubMed ID: 35143521
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning approaches to surrogate multifidelity Growth and Remodeling models for efficient abdominal aortic aneurysmal applications.
    Jiang Z; Choi J; Baek S
    Comput Biol Med; 2021 Jun; 133():104394. PubMed ID: 34015599
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Behavioural analysis of single-cell aneural ciliate,
    Trinh MK; Wayland MT; Prabakaran S
    J R Soc Interface; 2019 Dec; 16(161):20190410. PubMed ID: 31795860
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The potential for complex computational models of aging.
    Farrell S; Stubbings G; Rockwood K; Mitnitski A; Rutenberg A
    Mech Ageing Dev; 2021 Jan; 193():111403. PubMed ID: 33220267
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios.
    Herrgårdh T; Madai VI; Kelleher JD; Magnusson R; Gustafsson M; Milani L; Gennemark P; Cedersund G
    Neuroimage Clin; 2021; 31():102694. PubMed ID: 34000646
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes.
    Woldaregay AZ; Årsand E; Walderhaug S; Albers D; Mamykina L; Botsis T; Hartvigsen G
    Artif Intell Med; 2019 Jul; 98():109-134. PubMed ID: 31383477
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A New Surrogate-Assisted Interactive Genetic Algorithm With Weighted Semisupervised Learning.
    Sun X; Gong D; Jin Y; Chen S
    IEEE Trans Cybern; 2013 Apr; 43(2):685-98. PubMed ID: 23014759
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning approaches for analyzing and enhancing molecular dynamics simulations.
    Wang Y; Lamim Ribeiro JM; Tiwary P
    Curr Opin Struct Biol; 2020 Apr; 61():139-145. PubMed ID: 31972477
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multi-fidelity information fusion with concatenated neural networks.
    Pawar S; San O; Vedula P; Rasheed A; Kvamsdal T
    Sci Rep; 2022 Apr; 12(1):5900. PubMed ID: 35393511
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Computational Systems Biology of Morphogenesis.
    Ko JM; Mousavi R; Lobo D
    Methods Mol Biol; 2022; 2399():343-365. PubMed ID: 35604563
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology.
    Alexiadis A
    Artif Intell Med; 2019 Jul; 98():27-34. PubMed ID: 31521250
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Multi-fidelity surrogate modeling through hybrid machine learning for biomechanical and finite element analysis of soft tissues.
    Sajjadinia SS; Carpentieri B; Shriram D; Holzapfel GA
    Comput Biol Med; 2022 Sep; 148():105699. PubMed ID: 35715259
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The use of machine learning to discover regulatory networks controlling biological systems.
    Erbe R; Gore J; Gemmill K; Gaykalova DA; Fertig EJ
    Mol Cell; 2022 Jan; 82(2):260-273. PubMed ID: 35016036
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Mechanistic models versus machine learning, a fight worth fighting for the biological community?
    Baker RE; Peña JM; Jayamohan J; Jérusalem A
    Biol Lett; 2018 May; 14(5):. PubMed ID: 29769297
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.