 \beta, achieving the minimum likelihood of transcription by tuning skewness parameter \beta, achieving the higher likelihood of transcription by tuning non-Gaussianity index \alpha, and a bifurcation for transcription at the critical value \alpha = 1. We conduct a series of numerical experiments about `regulating' the likelihood of gene transcription by tuning asymmetric stable L\'evy noise parameters .
<meaning-changed>  \beta, achieving the minimum likelihood of transcription by tuning skewness parameter \beta, achieving the higher likelihood of transcription by tuning non-Gaussianity index \alpha, and a bifurcation for transcription at the critical value \alpha = 1. We conduct a series of numerical experiments about `regulating' the likelihood of gene transcription by tuning asymmetric stable L\'evy noise parameters .
 \beta, achieving the minimum likelihood of transcription by tuning skewness parameter \beta, achieving the higher likelihood of transcription by tuning non-Gaussianity index \alpha, and a bifurcation for transcription at the critical value \alpha = 1 (i.e., beyond which the likelihood for transcription suddenly increases), and achieving a turning point at the threshold value \beta \approx 0.55 (i.e., beyond which the likelihood for transcription reversed for \alpha values). The bifurcation and turning point phenomena do not occur in the symmetric noise case (\beta =0). We conduct a series of numerical experiments about `regulating' the likelihood of gene transcription by tuning asymmetric stable L\'evy noise parameters .