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 *

137 related articles for article (PubMed ID: 30824905)

  • 21. PIntMF: Penalized Integrative Matrix Factorization method for multi-omics data.
    Pierre-Jean M; Mauger F; Deleuze JF; Le Floch E
    Bioinformatics; 2022 Jan; 38(4):900-907. PubMed ID: 34849583
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data.
    Wang H; Lengerich BJ; Aragam B; Xing EP
    Bioinformatics; 2019 Apr; 35(7):1181-1187. PubMed ID: 30184048
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Intervention in prediction measure: a new approach to assessing variable importance for random forests.
    Epifanio I
    BMC Bioinformatics; 2017 May; 18(1):230. PubMed ID: 28464827
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Integrating biological knowledge and gene expression data using pathway-guided random forests: a benchmarking study.
    Seifert S; Gundlach S; Junge O; Szymczak S
    Bioinformatics; 2020 Aug; 36(15):4301-4308. PubMed ID: 32399562
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Large-scale benchmark study of survival prediction methods using multi-omics data.
    Herrmann M; Probst P; Hornung R; Jurinovic V; Boulesteix AL
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32823283
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prediction of mutation effects using a deep temporal convolutional network.
    Kim HY; Kim D
    Bioinformatics; 2020 Apr; 36(7):2047-2052. PubMed ID: 31746978
    [TBL] [Abstract][Full Text] [Related]  

  • 27. PPTPP: a novel therapeutic peptide prediction method using physicochemical property encoding and adaptive feature representation learning.
    Zhang YP; Zou Q
    Bioinformatics; 2020 Jul; 36(13):3982-3987. PubMed ID: 32348463
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Predicting runtimes of bioinformatics tools based on historical data: five years of Galaxy usage.
    Tyryshkina A; Coraor N; Nekrutenko A
    Bioinformatics; 2019 Sep; 35(18):3453-3460. PubMed ID: 30698642
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Using recursive feature elimination in random forest to account for correlated variables in high dimensional data.
    Darst BF; Malecki KC; Engelman CD
    BMC Genet; 2018 Sep; 19(Suppl 1):65. PubMed ID: 30255764
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Exploring the variable importance in random forests under correlations: a general concept applied to donor organ quality in post-transplant survival.
    Wies C; Miltenberger R; Grieser G; Jahn-Eimermacher A
    BMC Med Res Methodol; 2023 Sep; 23(1):209. PubMed ID: 37726680
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Integrating multi-OMICS data through sparse canonical correlation analysis for the prediction of complex traits: a comparison study.
    Rodosthenous T; Shahrezaei V; Evangelou M
    Bioinformatics; 2020 Nov; 36(17):4616-4625. PubMed ID: 32437529
    [TBL] [Abstract][Full Text] [Related]  

  • 32. TaxoNN: ensemble of neural networks on stratified microbiome data for disease prediction.
    Sharma D; Paterson AD; Xu W
    Bioinformatics; 2020 Nov; 36(17):4544-4550. PubMed ID: 32449747
    [TBL] [Abstract][Full Text] [Related]  

  • 33. On what to permute in test-based approaches for variable importance measures in Random Forests.
    Nembrini S
    Bioinformatics; 2019 Aug; 35(15):2701-2705. PubMed ID: 30561510
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Prediction of
    Ingrisch M; Schöppe F; Paprottka K; Fabritius M; Strobl FF; De Toni EN; Ilhan H; Todica A; Michl M; Paprottka PM
    J Nucl Med; 2018 May; 59(5):769-773. PubMed ID: 29146692
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Estimating and testing the microbial causal mediation effect with high-dimensional and compositional microbiome data.
    Wang C; Hu J; Blaser MJ; Li H
    Bioinformatics; 2020 Jan; 36(2):347-355. PubMed ID: 31329243
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Random KNN feature selection - a fast and stable alternative to Random Forests.
    Li S; Harner EJ; Adjeroh DA
    BMC Bioinformatics; 2011 Nov; 12():450. PubMed ID: 22093447
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Use and misuse of random forest variable importance metrics in medicine: demonstrations through incident stroke prediction.
    Wallace ML; Mentch L; Wheeler BJ; Tapia AL; Richards M; Zhou S; Yi L; Redline S; Buysse DJ
    BMC Med Res Methodol; 2023 Jun; 23(1):144. PubMed ID: 37337173
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A deep learning architecture for metabolic pathway prediction.
    Baranwal M; Magner A; Elvati P; Saldinger J; Violi A; Hero AO
    Bioinformatics; 2020 Apr; 36(8):2547-2553. PubMed ID: 31879763
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Dealing with dimensionality: the application of machine learning to multi-omics data.
    Feldner-Busztin D; Firbas Nisantzis P; Edmunds SJ; Boza G; Racimo F; Gopalakrishnan S; Limborg MT; Lahti L; de Polavieja GG
    Bioinformatics; 2023 Feb; 39(2):. PubMed ID: 36637211
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Adjusting for covariates and assessing modeling fitness in machine learning using MUVR2.
    Yan Y; Schillemans T; Skantze V; Brunius C
    Bioinform Adv; 2024; 4(1):vbae051. PubMed ID: 38645717
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.