Last modified on 24 August 2012.
Shang L., Xu W., Ozer S., and Gutell R.R. (2012).
Structural Constraints Identified with Covariation Analysis in Ribosomal RNA.
PLoS ONE, 7(6):e39383.
|Figures||Figure 1. The highlight and underlying concepts of the PEC based covariation analysis in rCAD.||PDF | TIF|
|Figure 2. The flowchart of analysis in the identification of base-pairs and neighbor effects.||PDF | TIF|
|Figure 3. The precision of top N ranked prediction plot with different covariation methods in the identification of base pairs using different data sets.||PDF | TIF|
|Figure 4. The number of true positives and false positives identified in different methods.||PDF | TIF|
|Figure 5. The base pairs (true positives) identified by PEC/JN-Best and MI/JN-Best are plotted onto the T. thermophilus 16S rRNA secondary structure diagram.||PDF | TIF|
|Figure 6. For each method, the number of true positives and false positives identified in the Joint N-Best calculation (nucleation pairs), following helix extension procedure (extended pairs), and sum of them are shown as a stacked histogram.||PDF | TIF|
|Figure 7. Base pairs in the Bacterial 16S rRNA structure model that are identified with the helix extension method.||PDF | TIF|
|Figure 8. The distribution of purity score and average conservation (or informational entropy) for the two nucleotides that form a base pair.||PDF | TIF|
|Figure 9. The secondary structural diagram of T. thermophilus 16S rRNA reveals all identified neighbor effects.||PDF | TIF|
Supplemental Figures and Tables:
|Data||Supplemental Dataset S1. The bacterial 16S rRNA sequence alignment used in this analysis.||FASTA|
|Supplemental Dataset S2. The bacterial 23S rRNA sequence alignment used in this analysis.||FASTA|
|Supplemental Dataset S3. The bacterial 5S rRNA sequence alignment used in this analysis.||FASTA|
|Figures||Supplemental Figure S1. Pseudo code of phylogenetic event counting algorithm.||PDF | TIF|
|Supplemental Figure S2. Variation/covariation analysis of the secondary structure of the bacterial 16S rRNA sequence alignment.||PDF | TIF|
|Supplemental Figure S3. Graphical representation of N-Best method.||PDF | TIF|
|Supplemental Figure S4. The secondary (A) and three-dimensional structure (B) of S. cerevisiae Phe tRNA with neighbor effect identified in 1992.||PDF | TIF|
|Supplemental Figure S5. The underlying principle of coarse filter that reduce the number of pairwise comparison.||PDF | TIF|
|Supplemental Figure S6. Base pairs in the Bacterial 16S rRNA structure model that are identified with the helix extension method using different nucleation pairs.||PDF | TIF|
|Supplemental Figure S7. Example of the determination of a purity score.||PDF | TIF|
|Supplemental Figure S8. The maximal distance between the positions defined to be a neighbor effect is determined from a comparison of the number of phylogenetic events.||PDF | TIF|
|Supplemental Figure Legends.||HTML|
|Tables||Supplemental Table 1. The phylogenetic distribution and sequence similarities of the 16S, 5S and 23S rRNA datasets used in analysis.||XLS|
|Supplemental Table 2. Detail information about all 14276 pairs of columns process in Phylogenetic Event Counting analysis on 16S rRNA data set.||XLS|
|Supplemental Table 3. The unique and common pairs identified by PEC/JN-Best, MIxy/JN-Best and MIp/JN-Best using the 16S, 5S and 23S rRNA data sets.||XLS|
|Supplemental Table 4. The complete list of nucleation pairs and extended pairs involved in the Helix Extension analysis on the 16S, 5S and 23S rRNA data sets.||XLS|
|Supplemental Table 5. A complete list of neighbor effects identified with our analysis.||XLS|
|Supplemental Table 6. The evaluation of the "new putative interactions in 16S rRNA" discovered by 2 other groups.||XLS|