| Chapter title |
RNA Structure Determination
|
|---|---|
| Chapter number | 13 |
| Book title |
RNA Structure Determination
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-6433-8_13 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6431-4, 978-1-4939-6433-8
|
| Authors |
Biesiada, Marcin, Purzycka, Katarzyna J, Szachniuk, Marta, Blazewicz, Jacek, Adamiak, Ryszard W, Marcin Biesiada, Katarzyna J. Purzycka, Marta Szachniuk, Jacek Blazewicz, Ryszard W. Adamiak |
| Abstract |
RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure. RNAComposer method is especially suited for structural biology users. Since our initial report in 2012, both servers, freely available at http://rnacomposer.ibch.poznan.pl and http://rnacomposer.cs.put.poznan.pl have been often visited. Therefore this chapter provides guidance for using RNAComposer and discusses points that should be considered when predicting 3D RNA structure. An application example presents current scope and limitations of RNAComposer. |
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| United States | 1 | 25% |
| France | 1 | 25% |
| Turkey | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
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| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 85 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 20% |
| Student > Bachelor | 13 | 15% |
| Researcher | 10 | 12% |
| Student > Master | 6 | 7% |
| Student > Doctoral Student | 3 | 4% |
| Other | 3 | 4% |
| Unknown | 33 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 22 | 26% |
| Agricultural and Biological Sciences | 7 | 8% |
| Chemistry | 5 | 6% |
| Computer Science | 4 | 5% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 4% |
| Other | 7 | 8% |
| Unknown | 37 | 44% |