Accurate SHAPE-directed RNA structure determination
By Katherine E Deigan, Tian W Li, D. Mathews, Kevin M. Weeks. Proceedings of the National Academy of Sciences of the United States of America, 2009
705 citations recorded by the source corpus.
Subfields: Materials Chemistry, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/45ee407cc804b9e84098ca36fe1d409785a9524c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Materials Chemistry
- Christopher W. Leonard
- Jessica S. Reuter
- D. Mathews
- Shankar Balasubramanian
- A. Bugaut
- Greggory M. Rice
- Stanislav Bellaousov
- Kevin M. Weeks
In Molecular Biology
- Jessica S. Reuter
- Stanislav Bellaousov
- Christopher W. Leonard
- D. Mathews
- Greggory M. Rice
- Kevin M. Weeks
- A. Bugaut
- Matthew G. Seetin
Citations in the corpus
- 5′-UTR RNA G-quadruplexes: translation regulation and targeting (2012, methodology): “The application and refinement of such approaches and other methods, including SHAPE and CLIP-SEQ (138,139), could shed light on the existence and nature of RNA G-quadruplexes in cells.”
- Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots (2013, methodology): “Our original SHAPE-directed algorithm did not allow for pseudoknotted base pairs (15).”
- RNAstructure: web servers for RNA secondary structure prediction and analysis (2013, methodology): “For Fold, partition and Predict a Secondary Structure, structure prediction can be restrained using SHAPE mapping data, when available, to improve the accuracy of structure prediction (39).”
- RNA secondary structure modeling at consistent high accuracy using differential SHAPE (2014, methodology): “Due to the higher information content of the NMIA – 1M6 analysis, we recommend using three reagents γ have chosen to use the original log-function for incorporating 1M7 data into SHAPE-directed structure modeling”
- RNAstructure: software for RNA secondary structure prediction and analysis (2010, methodology): “Experimental data, such as enzymatic cleavage [13], chemical mapping [14], oligo-nucleotide array binding [28], SHAPE [29], and NMR data [30] can all be used to improve structure prediction accuracy.”
- Automated 3D structure composition for large RNAs (2012, background): “In recent years, attempts have been made to incorporate the structure probing data to improve the accuracy of the in silico RNA secondary structure predictions (5,6,42) especially in case of large RNA structures.”