BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

212 related articles for article (PubMed ID: 33676405)

  • 1. R.ROSETTA: an interpretable machine learning framework.
    Garbulowski M; Diamanti K; Smolińska K; Baltzer N; Stoll P; Bornelöv S; Øhrn A; Feuk L; Komorowski J
    BMC Bioinformatics; 2021 Mar; 22(1):110. PubMed ID: 33676405
    [TBL] [Abstract][Full Text] [Related]  

  • 2. MIDGET:Detecting differential gene expression on microarray data.
    Angelescu R; Dobrescu R
    Comput Methods Programs Biomed; 2021 Nov; 211():106418. PubMed ID: 34555591
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Explainable AI for Bioinformatics: Methods, Tools and Applications.
    Karim MR; Islam T; Shajalal M; Beyan O; Lange C; Cochez M; Rebholz-Schuhmann D; Decker S
    Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37478371
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Fast and interpretable genomic data analysis using multiple approximate kernel learning.
    Bektaş AB; Ak Ç; Gönen M
    Bioinformatics; 2022 Jun; 38(Suppl 1):i77-i83. PubMed ID: 35758810
    [TBL] [Abstract][Full Text] [Related]  

  • 5. treeheatr: an R package for interpretable decision tree visualizations.
    Le TT; Moore JH
    Bioinformatics; 2021 Apr; 37(2):282-284. PubMed ID: 32702108
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SMILE: systems metabolomics using interpretable learning and evolution.
    Sha C; Cuperlovic-Culf M; Hu T
    BMC Bioinformatics; 2021 May; 22(1):284. PubMed ID: 34049495
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder.
    Garbulowski M; Smolinska K; Diamanti K; Pan G; Maqbool K; Feuk L; Komorowski J
    Front Genet; 2021; 12():618277. PubMed ID: 33719335
    [TBL] [Abstract][Full Text] [Related]  

  • 8. fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies.
    Lin J; Sibley A; Shterev I; Nixon A; Innocenti F; Chan C; Owzar K
    BMC Bioinformatics; 2019 Jun; 20(1):333. PubMed ID: 31195980
    [TBL] [Abstract][Full Text] [Related]  

  • 9. RRegrs: an R package for computer-aided model selection with multiple regression models.
    Tsiliki G; Munteanu CR; Seoane JA; Fernandez-Lozano C; Sarimveis H; Willighagen EL
    J Cheminform; 2015; 7():46. PubMed ID: 26379782
    [TBL] [Abstract][Full Text] [Related]  

  • 10. dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.
    Cao H; Zhang Y; Baumbach J; Burton PR; Dwyer D; Koutsouleris N; Matschinske J; Marcon Y; Rajan S; Rieg T; Ryser-Welch P; Späth J; ; Herrmann C; Schwarz E
    Bioinformatics; 2022 Oct; 38(21):4919-4926. PubMed ID: 36073911
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Interpretable Decision Sets: A Joint Framework for Description and Prediction.
    Lakkaraju H; Bach SH; Jure L
    KDD; 2016 Aug; 2016():1675-1684. PubMed ID: 27853627
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine learning algorithms for outcome prediction in (chemo)radiotherapy: An empirical comparison of classifiers.
    Deist TM; Dankers FJWM; Valdes G; Wijsman R; Hsu IC; Oberije C; Lustberg T; van Soest J; Hoebers F; Jochems A; El Naqa I; Wee L; Morin O; Raleigh DR; Bots W; Kaanders JH; Belderbos J; Kwint M; Solberg T; Monshouwer R; Bussink J; Dekker A; Lambin P
    Med Phys; 2018 Jul; 45(7):3449-3459. PubMed ID: 29763967
    [TBL] [Abstract][Full Text] [Related]  

  • 13. MDITRE: Scalable and Interpretable Machine Learning for Predicting Host Status from Temporal Microbiome Dynamics.
    Maringanti VS; Bucci V; Gerber GK
    mSystems; 2022 Oct; 7(5):e0013222. PubMed ID: 36069455
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.
    Vougas K; Sakellaropoulos T; Kotsinas A; Foukas GP; Ntargaras A; Koinis F; Polyzos A; Myrianthopoulos V; Zhou H; Narang S; Georgoulias V; Alexopoulos L; Aifantis I; Townsend PA; Sfikakis P; Fitzgerald R; Thanos D; Bartek J; Petty R; Tsirigos A; Gorgoulis VG
    Pharmacol Ther; 2019 Nov; 203():107395. PubMed ID: 31374225
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predictive and interpretable models via the stacked elastic net.
    Rauschenberger A; Glaab E; van de Wiel MA
    Bioinformatics; 2021 Aug; 37(14):2012-2016. PubMed ID: 32437519
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Survival prediction models: an introduction to discrete-time modeling.
    Suresh K; Severn C; Ghosh D
    BMC Med Res Methodol; 2022 Jul; 22(1):207. PubMed ID: 35883032
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A General-Purpose Machine Learning R Library for Sparse Kernels Methods With an Application for Genome-Based Prediction.
    Montesinos López OA; Mosqueda González BA; Palafox González A; Montesinos López A; Crossa J
    Front Genet; 2022; 13():887643. PubMed ID: 35719365
    [TBL] [Abstract][Full Text] [Related]  

  • 18. eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models.
    Candia J; Tsang JS
    BMC Bioinformatics; 2019 Apr; 20(1):189. PubMed ID: 30991955
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multiple-kernel learning for genomic data mining and prediction.
    Wilson CM; Li K; Yu X; Kuan PF; Wang X
    BMC Bioinformatics; 2019 Aug; 20(1):426. PubMed ID: 31416413
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Interpretable machine learning methods for predictions in systems biology from omics data.
    Sidak D; Schwarzerová J; Weckwerth W; Waldherr S
    Front Mol Biosci; 2022; 9():926623. PubMed ID: 36387282
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.