242 related articles for article (PubMed ID: 28734892)
1. Correlation between RNA-Seq and microarrays results using TCGA data.
Chen L; Sun F; Yang X; Jin Y; Shi M; Wang L; Shi Y; Zhan C; Wang Q
Gene; 2017 Sep; 628():200-204. PubMed ID: 28734892
[TBL] [Abstract][Full Text] [Related]
2. Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.
Miller JA; Menon V; Goldy J; Kaykas A; Lee CK; Smith KA; Shen EH; Phillips JW; Lein ES; Hawrylycz MJ
BMC Genomics; 2014 Feb; 15(1):154. PubMed ID: 24564186
[TBL] [Abstract][Full Text] [Related]
3. Comparison of microarrays and RNA-seq for gene expression analyses of dose-response experiments.
Black MB; Parks BB; Pluta L; Chu TM; Allen BC; Wolfinger RD; Thomas RS
Toxicol Sci; 2014 Feb; 137(2):385-403. PubMed ID: 24194394
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Comprehensive evaluation of AmpliSeq transcriptome, a novel targeted whole transcriptome RNA sequencing methodology for global gene expression analysis.
Li W; Turner A; Aggarwal P; Matter A; Storvick E; Arnett DK; Broeckel U
BMC Genomics; 2015 Dec; 16():1069. PubMed ID: 26673413
[TBL] [Abstract][Full Text] [Related]
6. Evaluating gene expression in C57BL/6J and DBA/2J mouse striatum using RNA-Seq and microarrays.
Bottomly D; Walter NA; Hunter JE; Darakjian P; Kawane S; Buck KJ; Searles RP; Mooney M; McWeeney SK; Hitzemann R
PLoS One; 2011 Mar; 6(3):e17820. PubMed ID: 21455293
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. A systematic comparison and evaluation of high density exon arrays and RNA-seq technology used to unravel the peripheral blood transcriptome of sickle cell disease.
Raghavachari N; Barb J; Yang Y; Liu P; Woodhouse K; Levy D; O'Donnell CJ; Munson PJ; Kato GJ
BMC Med Genomics; 2012 Jun; 5():28. PubMed ID: 22747986
[TBL] [Abstract][Full Text] [Related]
9. Quantitative transcriptome analysis using RNA-seq.
Külahoglu C; Bräutigam A
Methods Mol Biol; 2014; 1158():71-91. PubMed ID: 24792045
[TBL] [Abstract][Full Text] [Related]
10. RNA Sequencing and Analysis.
Kukurba KR; Montgomery SB
Cold Spring Harb Protoc; 2015 Apr; 2015(11):951-69. PubMed ID: 25870306
[TBL] [Abstract][Full Text] [Related]
11. Analysis of Microarray and RNA-seq Expression Profiling Data.
Hung JH; Weng Z
Cold Spring Harb Protoc; 2017 Mar; 2017(3):. PubMed ID: 27574194
[TBL] [Abstract][Full Text] [Related]
12. Estimating accuracy of RNA-Seq and microarrays with proteomics.
Fu X; Fu N; Guo S; Yan Z; Xu Y; Hu H; Menzel C; Chen W; Li Y; Zeng R; Khaitovich P
BMC Genomics; 2009 Apr; 10():161. PubMed ID: 19371429
[TBL] [Abstract][Full Text] [Related]
13. Evaluation of the External RNA Controls Consortium (ERCC) reference material using a modified Latin square design.
Pine PS; Munro SA; Parsons JR; McDaniel J; Lucas AB; Lozach J; Myers TG; Su Q; Jacobs-Helber SM; Salit M
BMC Biotechnol; 2016 Jun; 16(1):54. PubMed ID: 27342544
[TBL] [Abstract][Full Text] [Related]
14. Guidance for RNA-seq co-expression network construction and analysis: safety in numbers.
Ballouz S; Verleyen W; Gillis J
Bioinformatics; 2015 Jul; 31(13):2123-30. PubMed ID: 25717192
[TBL] [Abstract][Full Text] [Related]
15. How to analyze gene expression using RNA-sequencing data.
Ramsköld D; Kavak E; Sandberg R
Methods Mol Biol; 2012; 802():259-74. PubMed ID: 22130886
[TBL] [Abstract][Full Text] [Related]
16. RNA-Seq Atlas--a reference database for gene expression profiling in normal tissue by next-generation sequencing.
Krupp M; Marquardt JU; Sahin U; Galle PR; Castle J; Teufel A
Bioinformatics; 2012 Apr; 28(8):1184-5. PubMed ID: 22345621
[TBL] [Abstract][Full Text] [Related]
17. RNA sequencing atopic dermatitis transcriptome profiling provides insights into novel disease mechanisms with potential therapeutic implications.
Suárez-Fariñas M; Ungar B; Correa da Rosa J; Ewald DA; Rozenblit M; Gonzalez J; Xu H; Zheng X; Peng X; Estrada YD; Dillon SR; Krueger JG; Guttman-Yassky E
J Allergy Clin Immunol; 2015 May; 135(5):1218-27. PubMed ID: 25840722
[TBL] [Abstract][Full Text] [Related]
18. Integration of RNA-Seq data with heterogeneous microarray data for breast cancer profiling.
Castillo D; Gálvez JM; Herrera LJ; Román BS; Rojas F; Rojas I
BMC Bioinformatics; 2017 Nov; 18(1):506. PubMed ID: 29157215
[TBL] [Abstract][Full Text] [Related]
19. Seq-ing improved gene expression estimates from microarrays using machine learning.
Korir PK; Geeleher P; Seoighe C
BMC Bioinformatics; 2015 Sep; 16():286. PubMed ID: 26338512
[TBL] [Abstract][Full Text] [Related]
20. Computational analysis of RNA-seq.
Givan SA; Bottoms CA; Spollen WG
Methods Mol Biol; 2012; 883():201-19. PubMed ID: 22589136
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]