We present a computational method for operon prediction based on a comparative genomics approach. A group of consecutive genes is considered as a candidate operon if both their gene sequences and functions are conserved across several phylogenetically related genomes. In addition, various supporting data for operons are also collected through the application of public domain computer programs, and used in our prediction method. These include the prediction of conserved gene functions, promoter motifs and terminators. An apparent advantage of our approach over other operon prediction methods is that it does not require many experimental data (such as gene expression data and pathway data) as input. This feature makes it applicable to many newly sequenced genomes that do not have extensive experimental information. In order to validate our prediction, we have tested the method on Escherichia coli K12, in which operon structures have been extensively studied, through a comparative analysis against Haemophilus influenzae Rd and Salmonella typhimurium LT2. Our method successfully predicted most of the 237 known operons. After this initial validation, we then applied the method to a newly sequenced and annotated microbial genome, Synechococcus sp. WH8102, through a comparative genome analysis with two other cyanobacterial genomes, Prochlorococcus marinus sp. MED4 and P.marinus sp. MIT9313. Our results are consistent with previously reported results and statistics on operons in the literature.
The absolute ionization probability of energetic ͑Ͼ500 eV͒ particles recoiled from Al͑100͒ by 2 and 5 keV Xe + bombardment was measured with time-of-flight spectroscopy. These values were then used to calibrate the energy and angular distributions of low-energy ͑10-600 eV͒ sputtered ions collected with an electrostatic analyzer. The independent-particle model of nonadiabatic surface-atom charge exchange, which is typically used to analyze single scattering events, was applied to the ion fractions of the recoiled and sputtered atoms. The model describes all the experimental data from a few eV to the keV range if a different surface electronic temperature is used for recoiling and sputtering. This suggests that the ionization process depends on the instantaneous surface condition at the time of ion emission.
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