BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

629 related articles for article (PubMed ID: 33794304)

  • 1. Using machine learning approaches for multi-omics data analysis: A review.
    Reel PS; Reel S; Pearson E; Trucco E; Jefferson E
    Biotechnol Adv; 2021; 49():107739. PubMed ID: 33794304
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Customizable Analysis Flow in Integrative Multi-Omics.
    Lancaster SM; Sanghi A; Wu S; Snyder MP
    Biomolecules; 2020 Nov; 10(12):. PubMed ID: 33260881
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Machine Learning-Based Approach Using Multi-omics Data to Predict Metabolic Pathways.
    Niranjan V; Uttarkar A; Kaul A; Varghese M
    Methods Mol Biol; 2023; 2553():441-452. PubMed ID: 36227554
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Machine learning: its challenges and opportunities in plant system biology.
    Hesami M; Alizadeh M; Jones AMP; Torkamaneh D
    Appl Microbiol Biotechnol; 2022 May; 106(9-10):3507-3530. PubMed ID: 35575915
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Systems biology in cardiovascular disease: a multiomics approach.
    Joshi A; Rienks M; Theofilatos K; Mayr M
    Nat Rev Cardiol; 2021 May; 18(5):313-330. PubMed ID: 33340009
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The Trifecta of Single-Cell, Systems-Biology, and Machine-Learning Approaches.
    Weiskittel TM; Correia C; Yu GT; Ung CY; Kaufmann SH; Billadeau DD; Li H
    Genes (Basel); 2021 Jul; 12(7):. PubMed ID: 34356114
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data.
    Drouard G; Mykkänen J; Heiskanen J; Pohjonen J; Ruohonen S; Pahkala K; Lehtimäki T; Wang X; Ollikainen M; Ripatti S; Pirinen M; Raitakari O; Kaprio J
    BMC Med Inform Decis Mak; 2024 May; 24(1):116. PubMed ID: 38698395
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Machine learning for multi-omics data integration in cancer.
    Cai Z; Poulos RC; Liu J; Zhong Q
    iScience; 2022 Feb; 25(2):103798. PubMed ID: 35169688
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Integration strategies of multi-omics data for machine learning analysis.
    Picard M; Scott-Boyer MP; Bodein A; Périn O; Droit A
    Comput Struct Biotechnol J; 2021; 19():3735-3746. PubMed ID: 34285775
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Integrate multi-omics data with biological interaction networks using Multi-view Factorization AutoEncoder (MAE).
    Ma T; Zhang A
    BMC Genomics; 2019 Dec; 20(Suppl 11):944. PubMed ID: 31856727
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.
    Acharya D; Mukhopadhyay A
    Brief Funct Genomics; 2024 Apr; ():. PubMed ID: 38600757
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Integrative omics - from data to biology.
    Dihazi H; Asif AR; Beißbarth T; Bohrer R; Feussner K; Feussner I; Jahn O; Lenz C; Majcherczyk A; Schmidt B; Schmitt K; Urlaub H; Valerius O
    Expert Rev Proteomics; 2018 Jun; 15(6):463-466. PubMed ID: 29757692
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine learning meets omics: applications and perspectives.
    Li R; Li L; Xu Y; Yang J
    Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34791021
    [TBL] [Abstract][Full Text] [Related]  

  • 14. From imaging a single cell to implementing precision medicine: an exciting new era.
    Karacosta LG
    Emerg Top Life Sci; 2021 Dec; 5(6):837-847. PubMed ID: 34889448
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Statistical and Machine-Learning Analyses in Nutritional Genomics Studies.
    Khorraminezhad L; Leclercq M; Droit A; Bilodeau JF; Rudkowska I
    Nutrients; 2020 Oct; 12(10):. PubMed ID: 33066636
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A critical review of machine-learning for "multi-omics" marine metabolite datasets.
    Manochkumar J; Cherukuri AK; Kumar RS; Almansour AI; Ramamoorthy S; Efferth T
    Comput Biol Med; 2023 Oct; 165():107425. PubMed ID: 37696182
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identifying Molecular Biomarkers for Diseases With Machine Learning Based on Integrative Omics.
    Shi K; Lin W; Zhao XM
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(6):2514-2525. PubMed ID: 32305934
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology.
    Yan J; Wang X
    Plant J; 2022 Sep; 111(6):1527-1538. PubMed ID: 35821601
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Omics technologies in allergy and asthma research: An EAACI position paper.
    Radzikowska U; Baerenfaller K; Cornejo-Garcia JA; Karaaslan C; Barletta E; Sarac BE; Zhakparov D; Villaseñor A; Eguiluz-Gracia I; Mayorga C; Sokolowska M; Barbas C; Barber D; Ollert M; Chivato T; Agache I; Escribese MM
    Allergy; 2022 Oct; 77(10):2888-2908. PubMed ID: 35713644
    [TBL] [Abstract][Full Text] [Related]  

  • 20.
    ; ; . PubMed ID:
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 32.