| Chapter title |
MicroRNAs, Regulatory Networks, and Comorbidities: Decoding Complex Systems
|
|---|---|
| Chapter number | 19 |
| Book title |
MicroRNA Detection and Target Identification
|
| Published in |
Methods in molecular biology, April 2017
|
| DOI | 10.1007/978-1-4939-6866-4_19 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6864-0, 978-1-4939-6866-4
|
| Authors |
Francesco Russo, Kirstine Belling, Anders Boeck Jensen, Flavia Scoyni, Søren Brunak, Marco Pellegrini, Russo, Francesco, Belling, Kirstine, Jensen, Anders Boeck, Scoyni, Flavia, Brunak, Søren, Pellegrini, Marco |
| Editors |
Tamas Dalmay |
| Abstract |
MicroRNAs (miRNAs) are small noncoding RNAs involved in the posttranscriptional regulation of messenger RNAs (mRNAs). Each miRNA targets a specific set of mRNAs. Upon binding the miRNA inhibits mRNA translation or facilitate mRNA degradation. miRNAs are frequently deregulated in several pathologies including cancer and cardiovascular diseases. Since miRNAs have a crucial role in fine-tuning the expression of their targets, they have been proposed as biomarkers of disease progression and prognostication.In this chapter we discuss different approaches for computational predictions of miRNA targets based on sequence complementarity and integration of expression data. In the last section of the chapter we discuss new opportunities in the study of miRNA regulatory networks in the context of temporal disease progression and comorbidities. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 2 | 33% |
| United States | 1 | 17% |
| France | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 2 | 33% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 31% |
| Student > Bachelor | 2 | 15% |
| Other | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Professor | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 3 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 31% |
| Agricultural and Biological Sciences | 2 | 15% |
| Nursing and Health Professions | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Neuroscience | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 4 | 31% |