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 *

195 related articles for article (PubMed ID: 31145724)

  • 1. Parameter estimation and identifiability in a neural population model for electro-cortical activity.
    Hartoyo A; Cadusch PJ; Liley DTJ; Hicks DG
    PLoS Comput Biol; 2019 May; 15(5):e1006694. PubMed ID: 31145724
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comprehensive benchmarking of Markov chain Monte Carlo methods for dynamical systems.
    Ballnus B; Hug S; Hatz K; Görlitz L; Hasenauer J; Theis FJ
    BMC Syst Biol; 2017 Jun; 11(1):63. PubMed ID: 28646868
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Universally sloppy parameter sensitivities in systems biology models.
    Gutenkunst RN; Waterfall JJ; Casey FP; Brown KS; Myers CR; Sethna JP
    PLoS Comput Biol; 2007 Oct; 3(10):1871-78. PubMed ID: 17922568
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Quantifying the uncertainty in model parameters using Gaussian process-based Markov chain Monte Carlo in cardiac electrophysiology.
    Dhamala J; Arevalo HJ; Sapp J; Horácek BM; Wu KC; Trayanova NA; Wang L
    Med Image Anal; 2018 Aug; 48():43-57. PubMed ID: 29843078
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Estimation of neural dynamics from MEG/EEG cortical current density maps: application to the reconstruction of large-scale cortical synchrony.
    David O; Garnero L; Cosmelli D; Varela FJ
    IEEE Trans Biomed Eng; 2002 Sep; 49(9):975-87. PubMed ID: 12214887
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Optimal Model Parameter Estimation from EEG Power Spectrum Features Observed during General Anesthesia.
    Hashemi M; Hutt A; Buhry L; Sleigh J
    Neuroinformatics; 2018 Apr; 16(2):231-251. PubMed ID: 29516302
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Ensemble inhibition and excitation in the human cortex: An Ising-model analysis with uncertainties.
    Zanoci C; Dehghani N; Tegmark M
    Phys Rev E; 2019 Mar; 99(3-1):032408. PubMed ID: 30999501
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Inferring a simple mechanism for alpha-blocking by fitting a neural population model to EEG spectra.
    Hartoyo A; Cadusch PJ; Liley DTJ; Hicks DG
    PLoS Comput Biol; 2020 Apr; 16(4):e1007662. PubMed ID: 32352973
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A neural mass model for the simulation of cortical activity estimated from high resolution EEG during cognitive or motor tasks.
    Zavaglia M; Astolfi L; Babiloni F; Ursino M
    J Neurosci Methods; 2006 Oct; 157(2):317-29. PubMed ID: 16757033
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Efficient Markov chain Monte Carlo methods for decoding neural spike trains.
    Ahmadian Y; Pillow JW; Paninski L
    Neural Comput; 2011 Jan; 23(1):46-96. PubMed ID: 20964539
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Reconstruction of extended cortical sources for EEG and MEG based on a Monte-Carlo-Markov-chain estimator.
    Kincses WE; Braun C; Kaiser S; Grodd W; Ackermann H; Mathiak K
    Hum Brain Mapp; 2003 Feb; 18(2):100-10. PubMed ID: 12518290
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Global nonlinear approach for mapping parameters of neural mass models.
    Dunstan DM; Richardson MP; Abela E; Akman OE; Goodfellow M
    PLoS Comput Biol; 2023 Mar; 19(3):e1010985. PubMed ID: 36961869
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparing variational Bayes with Markov chain Monte Carlo for Bayesian computation in neuroimaging.
    Nathoo FS; Lesperance ML; Lawson AB; Dean CB
    Stat Methods Med Res; 2013 Aug; 22(4):398-423. PubMed ID: 22642986
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Adaptive Stimulus Design for Dynamic Recurrent Neural Network Models.
    Doruk RO; Zhang K
    Front Neural Circuits; 2018; 12():119. PubMed ID: 30723397
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons.
    Buesing L; Bill J; Nessler B; Maass W
    PLoS Comput Biol; 2011 Nov; 7(11):e1002211. PubMed ID: 22096452
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Hamiltonian Monte Carlo methods for efficient parameter estimation in steady state dynamical systems.
    Kramer A; Calderhead B; Radde N
    BMC Bioinformatics; 2014 Jul; 15(1):253. PubMed ID: 25066046
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Proposing a two-level stochastic model for epileptic seizure genesis.
    Shayegh F; Sadri S; Amirfattahi R; Ansari-Asl K
    J Comput Neurosci; 2014 Feb; 36(1):39-53. PubMed ID: 23733322
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Markov chain Monte Carlo methods for state-space models with point process observations.
    Yuan K; Girolami M; Niranjan M
    Neural Comput; 2012 Jun; 24(6):1462-86. PubMed ID: 22364499
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian connective field modeling using a Markov Chain Monte Carlo approach.
    Invernizzi A; Haak KV; Carvalho JC; Renken RJ; Cornelissen FW
    Neuroimage; 2022 Dec; 264():119688. PubMed ID: 36280097
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Model-based measurement of epileptic tissue excitability.
    Frogerais P; Bellanger JJ; Wendling F
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():1578-81. PubMed ID: 18002272
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.