| Chapter title |
Discovery of RNA Motifs Using a Computational Pipeline that Allows Insertions in Paired Regions and Filtering of Candidate Sequences.
|
|---|---|
| Chapter number | 10 |
| Book title |
Ribozymes
|
| Published in |
Methods in molecular biology, February 2012
|
| DOI | 10.1007/978-1-61779-545-9_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-544-2, 978-1-61779-545-9
|
| Authors |
Jimenez RM, Rampášek L, Brejová B, Vinař T, Lupták A, Randi M. Jimenez, Ladislav Rampášek, Broňa Brejová, Tomáš Vinař, Andrej Lupták, Jimenez, Randi M., Rampášek, Ladislav, Brejová, Broňa, Vinař, Tomáš, Lupták, Andrej |
| Abstract |
The enormous impact of noncoding RNAs on biology and biotechnology has motivated the development of systematic approaches to their discovery and characterization. Here we present a methodology for reliable detection of genomic ribozymes that centers on pipelined structure-based searches, utilizing two versatile algorithms for structure prediction. RNArobo is a prototype structure-based search package that enables a single search to return all sequences matching a designated motif descriptor, taking into account the possibility of single nucleotide insertions within base-paired regions. These outputs are then filtered through a structure prediction algorithm based on free energy minimization in order to maximize the proportion of catalytically active RNA motifs. This pipeline provides a fast approach to uncovering new catalytic RNAs with known secondary structures and verifying their activity in vitro. |
X Demographics
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| Country | Count | As % |
|---|---|---|
| France | 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 | 12 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 33% |
| Student > Ph. D. Student | 3 | 25% |
| Student > Bachelor | 1 | 8% |
| Professor | 1 | 8% |
| Student > Master | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 1 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 42% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Computer Science | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Chemistry | 1 | 8% |
| Other | 1 | 8% |
| Unknown | 2 | 17% |