BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

201 related articles for article (PubMed ID: 34164114)

  • 1. RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.
    Ramos TAR; Galindo NRO; Arias-Carrasco R; da Silva CF; Maracaja-Coutinho V; do Rêgo TG
    F1000Res; 2021; 10():323. PubMed ID: 34164114
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Radiogenomics of lower-grade gliomas: machine learning-based MRI texture analysis for predicting 1p/19q codeletion status.
    Kocak B; Durmaz ES; Ates E; Sel I; Turgut Gunes S; Kaya OK; Zeynalova A; Kilickesmez O
    Eur Radiol; 2020 Feb; 30(2):877-886. PubMed ID: 31691122
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation of machine learning algorithms performance for the prediction of early multiple sclerosis from resting-state FMRI connectivity data.
    Saccà V; Sarica A; Novellino F; Barone S; Tallarico T; Filippelli E; Granata A; Chiriaco C; Bruno Bossio R; Valentino P; Quattrone A
    Brain Imaging Behav; 2019 Aug; 13(4):1103-1114. PubMed ID: 29992392
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Support Vector Machine based method to distinguish long non-coding RNAs from protein coding transcripts.
    Schneider HW; Raiol T; Brigido MM; Walter MEMT; Stadler PF
    BMC Genomics; 2017 Oct; 18(1):804. PubMed ID: 29047334
    [TBL] [Abstract][Full Text] [Related]  

  • 5. mSRFR: a machine learning model using microalgal signature features for ncRNA classification.
    Anuntakarun S; Lertampaiporn S; Laomettachit T; Wattanapornprom W; Ruengjitchatchawalya M
    BioData Min; 2022 Mar; 15(1):8. PubMed ID: 35313925
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Comparing Multiple Machine Learning Algorithms and Metrics for Estrogen Receptor Binding Prediction.
    Russo DP; Zorn KM; Clark AM; Zhu H; Ekins S
    Mol Pharm; 2018 Oct; 15(10):4361-4370. PubMed ID: 30114914
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Early Diabetes Prediction: A Comparative Study Using Machine Learning Techniques.
    Poly TN; Islam MM; Li YJ
    Stud Health Technol Inform; 2022 Jun; 295():409-413. PubMed ID: 35773898
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Nitrate Classification Based on Optical Absorbance Data Using Machine Learning Algorithms for a Hydroponics System.
    Sulaiman R; Azeman NH; Abu Bakar MH; Ahmad Nazri NA; Masran AS; Ashrif A Bakar A
    Appl Spectrosc; 2023 Feb; 77(2):210-219. PubMed ID: 36348500
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Large-scale comparison of machine learning algorithms for target prediction of natural products.
    Liang L; Liu Y; Kang B; Wang R; Sun MY; Wu Q; Meng XF; Lin JP
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36007240
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Prediction model development of late-onset preeclampsia using machine learning-based methods.
    Jhee JH; Lee S; Park Y; Lee SE; Kim YA; Kang SW; Kwon JY; Park JT
    PLoS One; 2019; 14(8):e0221202. PubMed ID: 31442238
    [TBL] [Abstract][Full Text] [Related]  

  • 11. CRlncRC: a machine learning-based method for cancer-related long noncoding RNA identification using integrated features.
    Zhang X; Wang J; Li J; Chen W; Liu C
    BMC Med Genomics; 2018 Dec; 11(Suppl 6):120. PubMed ID: 30598114
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Machine Learning Models Identify New Inhibitors for Human OATP1B1.
    Lane TR; Urbina F; Zhang X; Fye M; Gerlach J; Wright SH; Ekins S
    Mol Pharm; 2022 Nov; 19(11):4320-4332. PubMed ID: 36269563
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparing different supervised machine learning algorithms for disease prediction.
    Uddin S; Khan A; Hossain ME; Moni MA
    BMC Med Inform Decis Mak; 2019 Dec; 19(1):281. PubMed ID: 31864346
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade.
    Bektas CT; Kocak B; Yardimci AH; Turkcanoglu MH; Yucetas U; Koca SB; Erdim C; Kilickesmez O
    Eur Radiol; 2019 Mar; 29(3):1153-1163. PubMed ID: 30167812
    [TBL] [Abstract][Full Text] [Related]  

  • 15. CORAZON: a web server for data normalization and unsupervised clustering based on expression profiles.
    Ramos TAR; Maracaja-Coutinho V; Ortega JM; do Rêgo TG
    BMC Res Notes; 2020 Jul; 13(1):338. PubMed ID: 32665017
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Gradient boosting for Parkinson's disease diagnosis from voice recordings.
    Karabayir I; Goldman SM; Pappu S; Akbilgic O
    BMC Med Inform Decis Mak; 2020 Sep; 20(1):228. PubMed ID: 32933493
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Machine-learning techniques for the prediction of protein-protein interactions.
    Sarkar D; Saha S
    J Biosci; 2019 Sep; 44(4):. PubMed ID: 31502581
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of Machine Learning Algorithms in the Prediction of Hospitalized Patients with Schizophrenia.
    Góngora Alonso S; Marques G; Agarwal D; De la Torre Díez I; Franco-Martín M
    Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408133
    [TBL] [Abstract][Full Text] [Related]  

  • 19. PINC: A Tool for Non-Coding RNA Identification in Plants Based on an Automated Machine Learning Framework.
    Zhang X; Zhou X; Wan M; Xuan J; Jin X; Li S
    Int J Mol Sci; 2022 Oct; 23(19):. PubMed ID: 36233123
    [TBL] [Abstract][Full Text] [Related]  

  • 20. NeRNA: A negative data generation framework for machine learning applications of noncoding RNAs.
    Orhan ME; Demirci YM; Saçar Demirci MD
    Comput Biol Med; 2023 Jun; 159():106861. PubMed ID: 37075604
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.