| Chapter title |
ASPicDB: A Database Web Tool for Alternative Splicing Analysis
|
|---|---|
| Chapter number | 23 |
| Book title |
RNA Bioinformatics
|
| Published in |
Methods in molecular biology, December 2014
|
| DOI | 10.1007/978-1-4939-2291-8_23 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-2290-1, 978-1-4939-2291-8
|
| Authors |
Mattia D'Antonio, Tiziana Castrgnanò, Matteo Pallocca, Anna Maria D'Erchia, Ernesto Picardi, Graziano Pesole, Mattia D’Antonio, Anna Maria D’Erchia, D'Antonio M, Castrgnanò T, Pallocca M, D'Erchia AM, Picardi E, Pesole G |
| Editors |
Ernesto Picardi |
| Abstract |
Alternative splicing (AS) is a basic molecular phenomenon that increases the functional complexity of higher eukaryotic transcriptomes. Indeed, through AS individual gene loci can generate multiple RNAs from the same pre-mRNA. AS has been investigated in a variety of clinical and pathological studies, such as the transcriptome regulation in cancer. In human, recent works based on massive RNA sequencing indicate that >95 % of pre-mRNAs are processed to yield multiple transcripts. Given the biological relevance of AS, several computational efforts have been done leading to the implementation of novel algorithms and specific specialized databases. Here we describe the web application ASPicDB that allows the recovery of detailed biological information about the splicing mechanism. ASPicDB provides powerful querying systems to interrogate AS events at gene, transcript, and protein levels. Finally, ASPicDB includes web visualization instruments to browse and export results for further off-line analyses. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Student > Ph. D. Student | 4 | 33% |
| Professor | 1 | 8% |
| Student > Master | 1 | 8% |
| Student > Postgraduate | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 33% |
| Agricultural and Biological Sciences | 3 | 25% |
| Medicine and Dentistry | 2 | 17% |
| Computer Science | 1 | 8% |
| Unknown | 2 | 17% |