| Chapter title |
SECISearch3 and Seblastian: In-Silico Tools to Predict SECIS Elements and Selenoproteins
|
|---|---|
| Chapter number | 1 |
| Book title |
Selenoproteins
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7258-6_1 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7257-9, 978-1-4939-7258-6
|
| Authors |
Marco Mariotti, Mariotti, Marco |
| Abstract |
The computational identification of selenoprotein genes is complicated by the dual meaning of the UGA codon as stop and selenocysteine. SECIS elements are RNA structures essential for selenocysteine incorporation, which have been used as markers for selenoprotein genes in many bioinformatics studies. The most widely used tool for eukaryotic SECIS finding has been recently improved to its third generation, SECISearch3. This program is also a component of Seblastian, a pipeline for the identification of selenoprotein genes that employs SECIS finding as the first step. This chapter constitutes a practical guide to use SECISearch3 and Seblastian, which can be run via webservers at http://seblastian.crg.eu / or http://gladyshevlab.org/SelenoproteinPredictionServer/ . |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 20% |
| Student > Doctoral Student | 2 | 20% |
| Student > Postgraduate | 2 | 20% |
| Researcher | 1 | 10% |
| Unknown | 3 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 30% |
| Agricultural and Biological Sciences | 2 | 20% |
| Mathematics | 1 | 10% |
| Immunology and Microbiology | 1 | 10% |
| Medicine and Dentistry | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 2 | 20% |