The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Variation in RNA-Seq Transcriptome Profiles of Peripheral Whole Blood from Healthy Individuals with and without Globin Depletion
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Erythroid-specific miR-451a and miR-486-5p are two of the most dominant microRNAs in human peripheral blood.
“Erythroid-specific miR-451a and miR-486-5p are two of the most dominant microRNAs (miRNAs) in human peripheral blood.”
From Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries (2020) · cites this paper as [4]
Red blood cells contain highly abundant miRNAs including miR-486-5p and miR-451a.
“For example, in addition to globin mRNAs, red blood cells also contain highly abundant miRNAs including miR-486-5p and miR-451a (4,5).”
From Depletion of erythropoietic miR-486-5p and miR-451a improves detectability of rare microRNAs in peripheral blood-derived small RNA sequencing libraries (2020) · cites this paper as [4]
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Citations
Cites
An Abundance of Ubiquitously Expressed Genes Revealed by Tissue Transcriptome Sequence Data
Ramsköld, D., Wang, E. T., Burge, C. B., & Sandberg, R. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000598 · Cited by 820
Statistical Design and Analysis of RNA Sequencing Data
Auer, P. L., & Doerge, R. W. (2010) · Genetics · doi:10.1534/genetics.110.114983 · Cited by 393
The External RNA Controls Consortium: a progress report
The External RNA Controls Consortium (2005) · Nature Methods · doi:10.1038/nmeth1005-731 · Cited by 373
Flagged first, then by citations
Research works printed but not linked: 19
- C-C Liew, 2006, The peripheral blood transcriptome dynamically reflects system wide biology: a potential diagnostic tool, J Lab Clin Med, 147, 126, 10.1016/j.lab.2005.10.005 · DOI
- S Mohr, 2007, The peripheral-blood transcriptome: new insights into disease and risk assessment, Trends Mol Med, 13, 422, 10.1016/j.molmed.2007.08.003 · DOI
- S Brouard, 2007, Identification of a peripheral blood transcriptional biomarker panel associated with operational renal allograft tolerance, Proc Natl Acad Sci, 104, 15448, 10.1073/pnas.0705834104 · DOI
- OP Günther, 2009, Functional Genomic Analysis of Peripheral Blood During Early Acute Renal Allograft Rejection, Transplantation, 88, 942, 10.1097/TP.0b013e3181b7ccc6 · DOI
- D Lin, 2009, Whole Blood Genomic Biomarkers of Acute Cardiac Allograft Rejection, J Heart Lung Transplant, 28, 927, 10.1016/j.healun.2009.04.025 · DOI
- Z Hollander, 2010, Whole Blood Biomarkers of Acute Cardiac Allograft Rejection: Double-Crossing the Biopsy, Transplantation, 90, 1388, 10.1097/TP.0b013e3182003df6 · DOI
- A Mastrokolias, 2012, Increased sensitivity of next generation sequencing-based expression profiling after globin reduction in human blood RNA, BMC Genomics, 13, 28, 10.1186/1471-2164-13-28 · DOI
- A O'Loughlin, 2012, Transcriptomic analysis of the stress response to weaning at housing in bovine leukocytes using RNA-seq technology, BMC Genomics, 13, 250, 10.1186/1471-2164-13-250 · DOI
- J Liu, 2006, Effects of Globin mRNA Reduction Methods on Gene Expression Profiles from Whole Blood, J Mol Diagn, 8, 551, 10.2353/jmoldx.2006.060021 · DOI
- L Li, 2008, Interference of globin genes with biomarker discovery for allograft rejection in peripheral blood samples, Physiol Genomics, 32, 190, 10.1152/physiolgenomics.00216.2007 · DOI
- Raghavachari N, Xu X, Munson PJ, Gladwin MT (2009) Characterization of Whole Blood Gene Expression Profiles as a Sequel to Globin mRNA Reduction in Patients with Sickle Cell Disease. PLoS ONE 4. Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2714456/. Accessed 24 June 2013. · DOI
- SHY Kam, 2012, Peripheral Blood Gene Expression Changes during Allergen Inhalation Challenge in Atopic Asthmatic Individuals, J Asthma, 49, 219, 10.3109/02770903.2011.654300 · DOI
- C Trapnell, 2009, TopHat: discovering splice junctions with RNA-Seq, Bioinformatics, 25, 1105, 10.1093/bioinformatics/btp120 · DOI
- Roberts A, Pimentel H, Trapnell C, Pachter L (2011) Identification of novel transcripts in annotated genomes using RNA-Seq. Bioinformatics. Available: http://bioinformatics.oxfordjournals.org/content/early/2011/06/21/bioinformatics.btr355. Accessed 2012 October 25. · DOI
- H Li, 2009, The Sequence Alignment/Map format and SAMtools, Bioinformatics, 25, 2078, 10.1093/bioinformatics/btp352 · DOI · Paper page
- H Thorvaldsdóttir, 2013, Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration, Brief Bioinform, 14, 178, 10.1093/bib/bbs017 · DOI · Paper page
- MD Robinson, 2010, edgeR: a Bioconductor package for differential expression analysis of digital gene expression data, Bioinformatics, 26, 139, 10.1093/bioinformatics/btp616 · DOI · Paper page
- Wickham H (2009) Ggplot2: elegant graphics for data analysis. New York: Springer. 212 p. · DOI · Paper page
- AS Devonshire, 2010, Evaluation of external RNA controls for the standardisation of gene expression biomarker measurements, BMC Genomics, 11, 662, 10.1186/1471-2164-11-662 · DOI
Cited by
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Zaitsev, A., Chelushkin, M., Dyikanov, D., Cheremushkin, I., Shpak, B., Nomie, K., Zyrin, V., Nuzhdina, E., Lozinsky, Y., Zotova, A., et al. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.07.006 · Cited by 139
Bustin, S., & Nolan, T. (2017) · European Journal of Clinical Investigation · doi:10.1111/eci.12801 · Cited by 113
Juzenas, S., Lindqvist, C. M., Ito, G., Dolshanskaya, Y., Halfvarson, J., Franke, A., & Hemmrich-Stanisak, G. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa008 · Cited by 17
Metadata
- Authors
- Shin, H., Shannon, C. P., Fishbane, N., Ruan, J., Zhou, M., Balshaw, R., Wilson-McManus, J. E., Ng, R. T., McManus, B. M., Tebbutt, S. J., & for the PROOF Centre of Excellence Team
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-03-07
- Volume
- 9
- Issue
- 3
- Pages
- e91041
- ISSN
- 1932-6203
- PMC
- PMC3946641
- Cited by
- 87
- References
- 3
- Language
- en
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