BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1007 related articles for article (PubMed ID: 21903743)

  • 21. Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.
    Rai MF; Tycksen ED; Sandell LJ; Brophy RH
    J Orthop Res; 2018 Jan; 36(1):484-497. PubMed ID: 28749036
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Robust identification of differentially expressed genes from RNA-seq data.
    Shahjaman M; Manir Hossain Mollah M; Rezanur Rahman M; Islam SMS; Nurul Haque Mollah M
    Genomics; 2020 Mar; 112(2):2000-2010. PubMed ID: 31756426
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Modifying SAMseq to account for asymmetry in the distribution of effect sizes when identifying differentially expressed genes.
    Kotoka E; Orr M
    Stat Appl Genet Mol Biol; 2017 Nov; 16(5-6):291-312. PubMed ID: 29077555
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Using microarray-based subtyping methods for breast cancer in the era of high-throughput RNA sequencing.
    Pedersen CB; Nielsen FC; Rossing M; Olsen LR
    Mol Oncol; 2018 Dec; 12(12):2136-2146. PubMed ID: 30289602
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A comparison of RNA-Seq and high-density exon array for detecting differential gene expression between closely related species.
    Liu S; Lin L; Jiang P; Wang D; Xing Y
    Nucleic Acids Res; 2011 Jan; 39(2):578-88. PubMed ID: 20864445
    [TBL] [Abstract][Full Text] [Related]  

  • 26. EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics.
    Rallapalli G; Kemen EM; Robert-Seilaniantz A; Segonzac C; Etherington GJ; Sohn KH; MacLean D; Jones JD
    BMC Genomics; 2014 May; 15(1):341. PubMed ID: 24884414
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Nonparametric expression analysis using inferential replicate counts.
    Zhu A; Srivastava A; Ibrahim JG; Patro R; Love MI
    Nucleic Acids Res; 2019 Oct; 47(18):e105. PubMed ID: 31372651
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Measuring differential gene expression with RNA-seq: challenges and strategies for data analysis.
    Finotello F; Di Camillo B
    Brief Funct Genomics; 2015 Mar; 14(2):130-42. PubMed ID: 25240000
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Accurate estimation of expression levels of homologous genes in RNA-seq experiments.
    Paşaniuc B; Zaitlen N; Halperin E
    J Comput Biol; 2011 Mar; 18(3):459-68. PubMed ID: 21385047
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Improving Gene-Set Enrichment Analysis of RNA-Seq Data with Small Replicates.
    Yoon S; Kim SY; Nam D
    PLoS One; 2016; 11(11):e0165919. PubMed ID: 27829002
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling.
    Zhao W; He X; Hoadley KA; Parker JS; Hayes DN; Perou CM
    BMC Genomics; 2014 Jun; 15(1):419. PubMed ID: 24888378
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling.
    Bradford JR; Hey Y; Yates T; Li Y; Pepper SD; Miller CJ
    BMC Genomics; 2010 May; 11():282. PubMed ID: 20444259
    [TBL] [Abstract][Full Text] [Related]  

  • 33. DEGseq: an R package for identifying differentially expressed genes from RNA-seq data.
    Wang L; Feng Z; Wang X; Wang X; Zhang X
    Bioinformatics; 2010 Jan; 26(1):136-8. PubMed ID: 19855105
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Comparative evaluation of isoform-level gene expression estimation algorithms for RNA-seq and exon-array platforms.
    Dapas M; Kandpal M; Bi Y; Davuluri RV
    Brief Bioinform; 2017 Mar; 18(2):260-269. PubMed ID: 26944083
    [TBL] [Abstract][Full Text] [Related]  

  • 35. XBSeq2: a fast and accurate quantification of differential expression and differential polyadenylation.
    Liu Y; Wu P; Zhou J; Johnson-Pais TL; Lai Z; Chowdhury WH; Rodriguez R; Chen Y
    BMC Bioinformatics; 2017 Oct; 18(Suppl 11):384. PubMed ID: 28984183
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Validation of differential gene expression algorithms: application comparing fold-change estimation to hypothesis testing.
    Yanofsky CM; Bickel DR
    BMC Bioinformatics; 2010 Jan; 11():63. PubMed ID: 20109217
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Statistical analysis of high-density oligonucleotide arrays: a multiplicative noise model.
    Sásik R; Calvo E; Corbeil J
    Bioinformatics; 2002 Dec; 18(12):1633-40. PubMed ID: 12490448
    [TBL] [Abstract][Full Text] [Related]  

  • 38. trieFinder: an efficient program for annotating Digital Gene Expression (DGE) tags.
    Renaud G; LaFave MC; Liang J; Wolfsberg TG; Burgess SM
    BMC Bioinformatics; 2014 Oct; 15(1):329. PubMed ID: 25311246
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Comparing bioinformatic gene expression profiling methods: microarray and RNA-Seq.
    Mantione KJ; Kream RM; Kuzelova H; Ptacek R; Raboch J; Samuel JM; Stefano GB
    Med Sci Monit Basic Res; 2014 Aug; 20():138-42. PubMed ID: 25149683
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Fused inverse-normal method for integrated differential expression analysis of RNA-seq data.
    Prasad B; Li X
    BMC Bioinformatics; 2022 Aug; 23(1):320. PubMed ID: 35931958
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 51.