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As in both methods we used oligo dT 20 primers for the reverse transcription, only changes in the poly(A) length that shorten the poly(A) to less than 20 As were assessable.
For both methods, we used FDR 0.05 to call significant interactions.
For both methods, we used a pseudocount of one (for EM) for the splice junctions, which helps to control the variance of the estimates on small datasets.
For both methods, we used precalculated point spread function tables that describe the gaussian distance-dependent detector response of a point source in air.
For implementing both methods, we used a simple form of potential [ 26], consisting in two terms: one related to contact interactions and the other to the solvent accessibility (see Methods).
For both methods, we used information from all three sample types (Ctrl, KD1 and KD2) to determine the variance between biological replicates which was then used in the individual comparisons (e.g., Ctrl versus KD1).
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For both methods, we use a 5% significance level (a typical value for this type of tests [20]).
In both methods, we use FFT for calculating the discrete Fourier spectra of signals.
Therefore, for all the analyses and for both the methods, we used a bin size of 0.1 ms and a temporal window of 3 bins.
Both classification methods we used suggested that the on average dolphin-like signals provide better classification performance than porpoise-like signals.
For both transfection methods, we used 1.5 2 µg each of the reporter plasmids pGL3-13X, pGL3-Bax and pGL3-p21 in the presence or absence of pBABE puro p53 wt (0.6 0.75 µg) and pLSXN Ras val 12, or active mutants of the PI3K or Raf pathway (0.6 0.75 µg).
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both methods we generalized
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