BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

336 related articles for article (PubMed ID: 28185579)

  • 1. A fuzzy method for RNA-Seq differential expression analysis in presence of multireads.
    Consiglio A; Mencar C; Grillo G; Marzano F; Caratozzolo MF; Liuni S
    BMC Bioinformatics; 2016 Nov; 17(Suppl 12):345. PubMed ID: 28185579
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.
    Johnson BK; Scholz MB; Teal TK; Abramovitch RB
    BMC Bioinformatics; 2016 Feb; 17():66. PubMed ID: 26847232
    [TBL] [Abstract][Full Text] [Related]  

  • 3. aFold - using polynomial uncertainty modelling for differential gene expression estimation from RNA sequencing data.
    Yang W; Rosenstiel P; Schulenburg H
    BMC Genomics; 2019 May; 20(1):364. PubMed ID: 31077153
    [TBL] [Abstract][Full Text] [Related]  

  • 4. BM-map: Bayesian mapping of multireads for next-generation sequencing data.
    Ji Y; Xu Y; Zhang Q; Tsui KW; Yuan Y; Norris C; Liang S; Liang H
    Biometrics; 2011 Dec; 67(4):1215-24. PubMed ID: 21517792
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Differential expression analysis of RNA sequencing data by incorporating non-exonic mapped reads.
    Chen HI; Liu Y; Zou Y; Lai Z; Sarkar D; Huang Y; Chen Y
    BMC Genomics; 2015; 16 Suppl 7(Suppl 7):S14. PubMed ID: 26099631
    [TBL] [Abstract][Full Text] [Related]  

  • 6. deGPS is a powerful tool for detecting differential expression in RNA-sequencing studies.
    Chu C; Fang Z; Hua X; Yang Y; Chen E; Cowley AW; Liang M; Liu P; Lu Y
    BMC Genomics; 2015 Jun; 16(1):455. PubMed ID: 26070955
    [TBL] [Abstract][Full Text] [Related]  

  • 7. BM-Map: an efficient software package for accurately allocating multireads of RNA-sequencing data.
    Yuan Y; Norris C; Xu Y; Tsui KW; Ji Y; Liang H
    BMC Genomics; 2012; 13 Suppl 8(Suppl 8):S9. PubMed ID: 23281802
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq data.
    Yoon S; Nam D
    BMC Genomics; 2017 May; 18(1):408. PubMed ID: 28545404
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Differentially expressed genes from RNA-Seq and functional enrichment results are affected by the choice of single-end versus paired-end reads and stranded versus non-stranded protocols.
    Corley SM; MacKenzie KL; Beverdam A; Roddam LF; Wilkins MR
    BMC Genomics; 2017 May; 18(1):399. PubMed ID: 28535780
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An effective method to resolve ambiguous bisulfite-treated reads.
    Liu M; Xu Y
    BMC Bioinformatics; 2021 May; 22(1):283. PubMed ID: 34044763
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.
    Liu X; Shi X; Chen C; Zhang L
    BMC Bioinformatics; 2015 Oct; 16():332. PubMed ID: 26475308
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Conceptual Framework for Abundance Estimation of Genomic Targets in the Presence of Ambiguous Short Sequencing Reads.
    Górczak K; Claesen J; Burzykowski T
    J Comput Biol; 2020 Aug; 27(8):1232-1247. PubMed ID: 31895597
    [No Abstract]   [Full Text] [Related]  

  • 13. RNA-Seq gene expression estimation with read mapping uncertainty.
    Li B; Ruotti V; Stewart RM; Thomson JA; Dewey CN
    Bioinformatics; 2010 Feb; 26(4):493-500. PubMed ID: 20022975
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Differential gene expression analysis using coexpression and RNA-Seq data.
    Yang EW; Girke T; Jiang T
    Bioinformatics; 2013 Sep; 29(17):2153-61. PubMed ID: 23793751
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Polyester: simulating RNA-seq datasets with differential transcript expression.
    Frazee AC; Jaffe AE; Langmead B; Leek JT
    Bioinformatics; 2015 Sep; 31(17):2778-84. PubMed ID: 25926345
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Differential Expression Analysis of RNA-seq Reads: Overview, Taxonomy, and Tools.
    Chowdhury HA; Bhattacharyya DK; Kalita JK
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(2):566-586. PubMed ID: 30281477
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Differential expression analysis on RNA-Seq count data based on penalized matrix decomposition.
    Liu JX; Gao YL; Xu Y; Zheng CH; You J
    IEEE Trans Nanobioscience; 2014 Mar; 13(1):12-8. PubMed ID: 24594510
    [TBL] [Abstract][Full Text] [Related]  

  • 18. It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR.
    Lun AT; Chen Y; Smyth GK
    Methods Mol Biol; 2016; 1418():391-416. PubMed ID: 27008025
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq.
    Williams CR; Baccarella A; Parrish JZ; Kim CC
    BMC Bioinformatics; 2017 Jan; 18(1):38. PubMed ID: 28095772
    [TBL] [Abstract][Full Text] [Related]  

  • 20. LFCseq: a nonparametric approach for differential expression analysis of RNA-seq data.
    Lin B; Zhang LF; Chen X
    BMC Genomics; 2014; 15 Suppl 10(Suppl 10):S7. PubMed ID: 25560842
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.