Jumping genes

Especially plants Jumping genes (Transposon sites)... 

Transposons are sequences of DNA that can move to different positions within the genome (transposition) once called jumping genes , they are examples of mobile genetic material. 

In general terms, bacterial resistance to antibacterial agents can be considered as being either intrinsic (innate, a natural property) or acquired, for example, by mutation or by the acquisition of a plasmid or transposon (jumping gene) [105]. Resistance to mercury [103, 122-125] and to other cations and anions [103, 122, 123, 125] is well characterized. The mechanisms involved in resistance to some metals, including silver, are summarized in Table 7.1. 

Froth floatation circuits for mineral processing Maximization of both the recovery of the concentrated ore and valuable mineral content in the concentrated ore. NSGA-II with modified Jumping Gene operator Equality constraint was imposed on total floatation cell volume. Guria et al. (2005a)... 

Guria, C., Verma, M., Mehrotra, S. P. and Gupta, S. K. (2006). Simultaneous optimization of the performance of flotation circuits and their simplification using the jumping gene adaptations of genetic algorithm-II More complex problems, Int. J. Miner. Process, 79, pp. 149-166. 

Khosla, D. K., Gupta, S. K. and Saraf, D. N. (2007). Multi-objective optimization of fuel oil blending using the jumping gene adaptation of genetic algorithm. Fuel Process. Technol, 88, pp. 51-63. 

Multi-Objective Genetic Algorithm and Simulated Annealing with the Jumping Gene Adaptations... 

Keywords Genetic Algorithm, Simulated Annealing, Jumping Gene. 

More recently, another adaptation of jumping genes, NSGA-II-aJG, has been developed by Bhat et al. (2006) and Bhat (2007). In this fixed-length (fb binaries) JG adaptation, a probability, Pjg, is used to see if a chromosome is to be modified. If yes, a single site only is identified (randomly) in it, from location 1 to n hr - fb- The other end of the JG is selected/i, binaries beyond it. The sub-string of binaries in-between these... 

Application of the Jumping Gene Adaptations of NSGA-II and MOSA to Three Benchmark Problems... 

The use of the jumping gene operator (any of the adaptations) increases the randomness/diversity and, thus, usually gives better results. Among the various JG adaptations discussed above, the sJG adaptation is found to be better for the benchmark problems studied here. But the choice of a particular adaptation is problem-specific, e.g., in froth flotation circuits the mJG adaptation (Guria et al., 2005b) is found to be better. 

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