BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

167 related articles for article (PubMed ID: 26355518)

  • 1. Improved and Promising Identification of Human MicroRNAs by Incorporating a High-Quality Negative Set.
    Wei L; Liao M; Gao Y; Ji R; He Z; Zou Q
    IEEE/ACM Trans Comput Biol Bioinform; 2014; 11(1):192-201. PubMed ID: 26355518
    [TBL] [Abstract][Full Text] [Related]  

  • 2. iMiRNA-SSF: Improving the Identification of MicroRNA Precursors by Combining Negative Sets with Different Distributions.
    Chen J; Wang X; Liu B
    Sci Rep; 2016 Jan; 6():19062. PubMed ID: 26753561
    [TBL] [Abstract][Full Text] [Related]  

  • 3. TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.
    Bandyopadhyay S; Mitra R
    Bioinformatics; 2009 Oct; 25(20):2625-31. PubMed ID: 19692556
    [TBL] [Abstract][Full Text] [Related]  

  • 4. miRNA-dis: microRNA precursor identification based on distance structure status pairs.
    Liu B; Fang L; Chen J; Liu F; Wang X
    Mol Biosyst; 2015 Apr; 11(4):1194-204. PubMed ID: 25715848
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MiRANN: a reliable approach for improved classification of precursor microRNA using Artificial Neural Network model.
    Rahman ME; Islam R; Islam S; Mondal SI; Amin MR
    Genomics; 2012 Apr; 99(4):189-94. PubMed ID: 22349176
    [TBL] [Abstract][Full Text] [Related]  

  • 6. μHEM for identification of differentially expressed miRNAs using hypercuboid equivalence partition matrix.
    Paul S; Maji P
    BMC Bioinformatics; 2013 Sep; 14():266. PubMed ID: 24006840
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Improved Pre-miRNA Classification by Reducing the Effect of Class Imbalance.
    Zhong Y; Xuan P; Han K; Zhang W; Li J
    Biomed Res Int; 2015; 2015():960108. PubMed ID: 26640803
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine.
    Xue C; Li F; He T; Liu GP; Li Y; Zhang X
    BMC Bioinformatics; 2005 Dec; 6():310. PubMed ID: 16381612
    [TBL] [Abstract][Full Text] [Related]  

  • 9. High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.
    Stegmayer G; Yones C; Kamenetzky L; Milone DH
    IEEE/ACM Trans Comput Biol Bioinform; 2017; 14(6):1316-1326. PubMed ID: 27295687
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Predicting human microRNA precursors based on an optimized feature subset generated by GA-SVM.
    Wang Y; Chen X; Jiang W; Li L; Li W; Yang L; Liao M; Lian B; Lv Y; Wang S; Wang S; Li X
    Genomics; 2011 Aug; 98(2):73-8. PubMed ID: 21586321
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predicting novel microRNA: a comprehensive comparison of machine learning approaches.
    Stegmayer G; Di Persia LE; Rubiolo M; Gerard M; Pividori M; Yones C; Bugnon LA; Rodriguez T; Raad J; Milone DH
    Brief Bioinform; 2019 Sep; 20(5):1607-1620. PubMed ID: 29800232
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Ensemble-based classification approach for micro-RNA mining applied on diverse metagenomic sequences.
    ElGokhy SM; ElHefnawi M; Shoukry A
    BMC Res Notes; 2014 May; 7():286. PubMed ID: 24884968
    [TBL] [Abstract][Full Text] [Related]  

  • 13. mirExplorer: detecting microRNAs from genome and next generation sequencing data using the AdaBoost method with transition probability matrix and combined features.
    Guan DG; Liao JY; Qu ZH; Zhang Y; Qu LH
    RNA Biol; 2011; 8(5):922-34. PubMed ID: 21881406
    [TBL] [Abstract][Full Text] [Related]  

  • 14. microPred: effective classification of pre-miRNAs for human miRNA gene prediction.
    Batuwita R; Palade V
    Bioinformatics; 2009 Apr; 25(8):989-95. PubMed ID: 19233894
    [TBL] [Abstract][Full Text] [Related]  

  • 15. BosFinder: a novel pre-microRNA gene prediction algorithm in Bos taurus.
    Sadeghi B; Ahmadi H; Azimzadeh-Jamalkandi S; Nassiri MR; Masoudi-Nejad A
    Anim Genet; 2014 Aug; 45(4):479-84. PubMed ID: 24835488
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Cancer survival classification using integrated data sets and intermediate information.
    Kim S; Park T; Kon M
    Artif Intell Med; 2014 Sep; 62(1):23-31. PubMed ID: 24997860
    [TBL] [Abstract][Full Text] [Related]  

  • 17. MicroRNA transcription start site prediction with multi-objective feature selection.
    Bhattacharyya M; Feuerbach L; Bhadra T; Lengauer T; Bandyopadhyay S
    Stat Appl Genet Mol Biol; 2012 Jan; 11(1):Article 6. PubMed ID: 22499686
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automatic learning of pre-miRNAs from different species.
    O N Lopes Id; Schliep A; de L F de Carvalho AP
    BMC Bioinformatics; 2016 May; 17(1):224. PubMed ID: 27233515
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Identification of microRNA precursors using reduced and hybrid features.
    Khan A; Shah S; Wahid F; Khan FG; Jabeen S
    Mol Biosyst; 2017 Jul; 13(8):1640-1645. PubMed ID: 28686281
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Genetic algorithm-based efficient feature selection for classification of pre-miRNAs.
    Xuan P; Guo MZ; Wang J; Wang CY; Liu XY; Liu Y
    Genet Mol Res; 2011 Apr; 10(2):588-603. PubMed ID: 21491369
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.