- Course overview
- Search within this course
- Introduction
- Real-time PCR
- Microarrays
- What is Next Generation DNA Sequencing?
- RNA sequencing
- Biological interpretation of gene expression data
- Genotyping, epigenetic and DNA/RNA-protein interaction methods
- DNA/RNA-protein interactions
- Summary
- Quiz: Check your learning
- Your feedback
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- References
References
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2. Oberthuer, A., et al. (2010) Comparison of performance of one-color and two-color gene-expression analyses in predicting clinical endpoints of neuroblastoma patients. Pharmacogenomics J. 10: 258–266.
3. Petryszak, R., et al. (2014) Expression Atlas update–a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments. Nucleic Acids Res. 42: D926–D932.
4. Grant, G.R., et al. (2007) Analysis and management of microarray gene expression data. Current Protocols in Molecular Biology Chapter 19:Unit 19.6.
5. Ritchie, M.E., et al. (2015) limma powers differential expression analyses for RNA-sequencing and microarray. Nucleic Acids Res. 43: e47.
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12. Curtis, R.K., et al. (2005) Pathways to the analysis of microarray data. Trends in Biotechnology 23: 429-435.
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15. Escaramís, G., et al. (2015) A decade of structural variants: description, history and methods to detect structural variation. Briefings in Functional Genomics 14: 305-314.
16. Ennis, C. (2014) Epigenetics 101: a beginner’s guide to explaining everything. The Guardian newspaper.
17. Esteller, M. (2007) Cancer epigenomics: DNA methylomes and histone-modification maps. Nature Rev. Gen. 8: 286-298.
18. Kurdyukov, S. and Bullock, M. (2016) DNA Methylation Analysis: Choosing the Right Method. Biology 5.
19. Fu, Y., et al. (2014) Gene expression regulation mediated through reversible m⁶A RNA methylation. Nature Rev. Gen. 15: 293-306.
20. Kimura, H. (2013) Histone modifications for human epigenome analysis. Journal of Human Genetics 58: 439-445.
21. Milek, M., et al. (2010) Transcriptome-wide analysis of protein-RNA interactions using high-throughput sequencing. Seminars in Cell & Developmental Biology 23: 206-212.
22. Helwa, R. and Hoheisel, J.D. (2010) Analysis of DNA-protein interactions: from nitrocellulose filter binding assays to microarray studies. Analytical and Bioanalytical Chemistry 398: 2551-2561.
23. Ascano, M., et al. (2013) Multi-disciplinary methods to define RNA-protein interactions and regulatory networks. Curr Opin Genet Dev. 23: 20–28.
24. Riley, K.J. and Steitz, J.A. The “Observer Effect” in genome-wide surveys of protein-RNA interactions. Molecular Cell 49: 601-604.
25. John, A., et al. (2024) Assessing different next-generation sequencing technologies for wastewater-based epidemiology. Water research 267: 122465.
26. Bejaoui, S., et al. (2025) Comparison of Illumina and Oxford Nanopore sequencing data quality for Clostridioides difficile genome analysis and their application for epidemiological surveillance. BMC genomics 26.1: 92.