On probabilities. All web pages with transforming potential are noticed to become relatively short. The longest Z-forming regions located in any of those three sequences at s {0:06 contains 14 base pairs. In each of these sequences there is at least one predominant region whose probability of forming Z-DNA exceeds 70 . In pBR322 the largest peak has probability near 70 , and there are three other sites whose probabilities exceed 25 . Phage wX174 contains a single region, slightly longer than that in pBR322, whose transition probability is close to unity. Because this region is so dominant at this superhelix density, other portions of this sequence have only low probabilities of Z-formation. This dominance is a consequencePLoS Computational Biology | www.ploscompbiol.orgof this site having a highly favorable transition energy over a sufficiently long region. We compared the performance of SIBZ with those of Z-Hunt and Z-Catcher when run on these sequences [35,47,48]. The energies from Table 1 were used in all three programs. When ZHunt was applied to the pBR322 sequence it found one 15 bp long segment at location 1448 with a Z-score of 2444, and a 17 bp long segment at position 1407 with a Z-score of 1845. As shown in Fig. 2a, SIBZ also finds these two peaks to be the most dominant, with the segment at location 1448 having the higher transition probability. This agrees with the relative Z-score rankings provided by Z-Hunt. However, the relative probabilities of these two regions are not proportional to their Z-score. Moreover, SIBZ documents several other regions that also have significant transition probabilities that Z-Hunt does not identify. One sees that, PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/20151456 although the sites found by Z-Hunt agree with the major sites found by SIBZ, the latter provides more information regarding other Zsusceptible regions. The results from SIBZ, because they are expressed as transition probabilities of the fully competitive transition at the Sitravatinib web assumed superhelix density, are both more precise and more easily interpretable than are Z-scores. Z-Catcher does not identify any Z-susceptible regions in pBR322 at superhelix density s {0:06. At superhelix density s {0:075 it finds the two dominant segments at locations 1407 and 1448. ItStress Induced B-Z Transitions(a)(b)(c)Figure 2. The B-Z transition profiles calculated at superhelical density s {0:06 are plotted for three circular genomes: (a) the pBR322 plasmid, (b) bacteriophage wX 174, and (c) Bdellovibrio phage wMH2K. doi:10.1371/journal.pcbi.1001051.galso finds two other Z-segments at positions where no Z-forming potential is seen by the other algorithms. The segment at position 1448 is found to comprise 28 base pairs, which is significantly longer than predicted either by Z-Hunt or by SIBZ. Thus, the predictions of Z-Catcher seem to differ considerably from those of either Z-Hunt or SIBZ. The behavior of a B-Z transition varies significantly as the negative superhelical density is modified. In general, as {s is increased, larger numbers of transformed base pairs are required to relieve torsional stresses. If the most energetically susceptible region is sufficiently long, the most favored way to do this would be by extending the transition to encompass increasing amounts of this region. However, the most Z-susceptible regions in natural DNA sequences are usually relatively short, as is seen in these three sequences. In that case what commonly happens is that, as {s (and hence also the level of imposed stress) increas.