Chapter title |
microRNA Expression Profiling: Technologies, Insights, and Prospects.
|
---|---|
Chapter number | 21 |
Book title |
microRNA: Medical Evidence
|
Published in |
Advances in experimental medicine and biology, January 2015
|
DOI | 10.1007/978-3-319-22671-2_21 |
Pubmed ID | |
Book ISBNs |
978-3-31-922670-5, 978-3-31-922671-2
|
Authors |
Roden, Christine, Mastriano, Stephen, Wang, Nayi, Lu, Jun, Christine Roden, Stephen Mastriano, Nayi Wang, Jun Lu |
Editors |
Gaetano Santulli |
Abstract |
Since the early days of microRNA (miRNA) research, miRNA expression profiling technologies have provided important tools toward both better understanding of the biological functions of miRNAs and using miRNA expression as potential diagnostics. Multiple technologies, such as microarrays, next-generation sequencing, bead-based detection system, single-molecule measurements, and quantitative RT-PCR, have enabled accurate quantification of miRNAs and the subsequent derivation of key insights into diverse biological processes. As a class of ~22 nt long small noncoding RNAs, miRNAs present unique challenges in expression profiling that require careful experimental design and data analyses. We will particularly discuss how normalization and the presence of miRNA isoforms can impact data interpretation. We will present one example in which the consideration in data normalization has provided insights that helped to establish the global miRNA expression as a tumor suppressor. Finally, we discuss two future prospects of using miRNA profiling technologies to understand single cell variability and derive new rules for the functions of miRNA isoforms. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Austria | 1 | 33% |
United States | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Luxembourg | 1 | 7% |
Unknown | 13 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 43% |
Other | 2 | 14% |
Student > Bachelor | 1 | 7% |
Lecturer | 1 | 7% |
Student > Master | 1 | 7% |
Other | 1 | 7% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 5 | 36% |
Biochemistry, Genetics and Molecular Biology | 4 | 29% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
Neuroscience | 1 | 7% |
Chemistry | 1 | 7% |
Other | 0 | 0% |
Unknown | 2 | 14% |