| Chapter title |
MicroRNA Sequencing Data Analysis Toolkits
|
|---|---|
| Chapter number | 16 |
| Book title |
MicroRNA and Cancer
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7435-1_16 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7433-7, 978-1-4939-7435-1
|
| Authors |
Wei Wu, Wu, Wei |
| Abstract |
MicroRNA (miRNA) is a non-protein-coding small RNA molecule that negatively regulates gene expression by degradation of mRNA or suppression of mRNA translation. MiRNAs play important roles in biological processes such as cellular development, differentiation, proliferation, apoptosis and stem cell self-renewal and cancer development. The expression profile of microRNAs is tissue-, cell-type specific. PCR- and microarray-based arrays are the commonly used for differential expression of microRNAs between different diseased conditions. With the next-generation sequencing or massively parallel DNA sequencing technology advanced and the cost is plummeting, microRNAseq approach is widely used for the genome-wide discovery of known and unknown miRNA expression. However, the analysis of microRNAseq is computational expensive, here I provide guidelines and available tools for microRNAseq analysis. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 27% |
| Student > Bachelor | 3 | 27% |
| Student > Ph. D. Student | 2 | 18% |
| Other | 1 | 9% |
| Professor > Associate Professor | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 1 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 36% |
| Neuroscience | 2 | 18% |
| Chemistry | 1 | 9% |
| Computer Science | 1 | 9% |
| Unknown | 3 | 27% |