BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

329 related articles for article (PubMed ID: 28968634)

  • 1. SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data.
    Shi X; Wang X; Wang TL; Hilakivi-Clarke L; Clarke R; Xuan J
    Bioinformatics; 2018 Jan; 34(1):56-63. PubMed ID: 28968634
    [TBL] [Abstract][Full Text] [Related]  

  • 2. IntAPT: integrated assembly of phenotype-specific transcripts from multiple RNA-seq profiles.
    Shi X; Neuwald AF; Wang X; Wang TL; Hilakivi-Clarke L; Clarke R; Xuan J
    Bioinformatics; 2021 May; 37(5):650-658. PubMed ID: 33016988
    [TBL] [Abstract][Full Text] [Related]  

  • 3. rSeqNP: a non-parametric approach for detecting differential expression and splicing from RNA-Seq data.
    Shi Y; Chinnaiyan AM; Jiang H
    Bioinformatics; 2015 Jul; 31(13):2222-4. PubMed ID: 25717189
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Transcript Profiling Using Long-Read Sequencing Technologies.
    Bayega A; Wang YC; Oikonomopoulos S; Djambazian H; Fahiminiya S; Ragoussis J
    Methods Mol Biol; 2018; 1783():121-147. PubMed ID: 29767360
    [TBL] [Abstract][Full Text] [Related]  

  • 5. TIGAR: transcript isoform abundance estimation method with gapped alignment of RNA-Seq data by variational Bayesian inference.
    Nariai N; Hirose O; Kojima K; Nagasaki M
    Bioinformatics; 2013 Sep; 29(18):2292-9. PubMed ID: 23821651
    [TBL] [Abstract][Full Text] [Related]  

  • 6. SSP: an interval integer linear programming for de novo transcriptome assembly and isoform discovery of RNA-seq reads.
    Safikhani Z; Sadeghi M; Pezeshk H; Eslahchi C
    Genomics; 2013; 102(5-6):507-14. PubMed ID: 24161398
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Identifying differentially spliced genes from two groups of RNA-seq samples.
    Wang W; Qin Z; Feng Z; Wang X; Zhang X
    Gene; 2013 Apr; 518(1):164-70. PubMed ID: 23228854
    [TBL] [Abstract][Full Text] [Related]  

  • 9. CRNET: an efficient sampling approach to infer functional regulatory networks by integrating large-scale ChIP-seq and time-course RNA-seq data.
    Chen X; Gu J; Wang X; Jung JG; Wang TL; Hilakivi-Clarke L; Clarke R; Xuan J
    Bioinformatics; 2018 May; 34(10):1733-1740. PubMed ID: 29280996
    [TBL] [Abstract][Full Text] [Related]  

  • 10. NSMAP: a method for spliced isoforms identification and quantification from RNA-Seq.
    Xia Z; Wen J; Chang CC; Zhou X
    BMC Bioinformatics; 2011 May; 12():162. PubMed ID: 21575225
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Read-Split-Run: an improved bioinformatics pipeline for identification of genome-wide non-canonical spliced regions using RNA-Seq data.
    Bai Y; Kinne J; Donham B; Jiang F; Ding L; Hassler JR; Kaufman RJ
    BMC Genomics; 2016 Aug; 17 Suppl 7(Suppl 7):503. PubMed ID: 27556805
    [TBL] [Abstract][Full Text] [Related]  

  • 12. BADGE: a novel Bayesian model for accurate abundance quantification and differential analysis of RNA-Seq data.
    Gu J; Wang X; Halakivi-Clarke L; Clarke R; Xuan J
    BMC Bioinformatics; 2014; 15 Suppl 9(Suppl 9):S6. PubMed ID: 25252852
    [TBL] [Abstract][Full Text] [Related]  

  • 13. EBSeq-HMM: a Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments.
    Leng N; Li Y; McIntosh BE; Nguyen BK; Duffin B; Tian S; Thomson JA; Dewey CN; Stewart R; Kendziorski C
    Bioinformatics; 2015 Aug; 31(16):2614-22. PubMed ID: 25847007
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Detecting Multivariate Gene Interactions in RNA-Seq Data Using Optimal Bayesian Classification.
    Knight JM; Ivanov I; Triff K; Chapkin RS; Dougherty ER
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(2):484-493. PubMed ID: 26441451
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Network-Based Isoform Quantification with RNA-Seq Data for Cancer Transcriptome Analysis.
    Zhang W; Chang JW; Lin L; Minn K; Wu B; Chien J; Yong J; Zheng H; Kuang R
    PLoS Comput Biol; 2015 Dec; 11(12):e1004465. PubMed ID: 26699225
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. NPEBseq: nonparametric empirical bayesian-based procedure for differential expression analysis of RNA-seq data.
    Bi Y; Davuluri RV
    BMC Bioinformatics; 2013 Aug; 14():262. PubMed ID: 23981227
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Alternative Splicing Signatures in RNA-seq Data: Percent Spliced in (PSI).
    Schafer S; Miao K; Benson CC; Heinig M; Cook SA; Hubner N
    Curr Protoc Hum Genet; 2015 Oct; 87():11.16.1-11.16.14. PubMed ID: 26439713
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SimSeq: a nonparametric approach to simulation of RNA-sequence datasets.
    Benidt S; Nettleton D
    Bioinformatics; 2015 Jul; 31(13):2131-40. PubMed ID: 25725090
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Identifying differentially expressed transcripts from RNA-seq data with biological variation.
    Glaus P; Honkela A; Rattray M
    Bioinformatics; 2012 Jul; 28(13):1721-8. PubMed ID: 22563066
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.