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Table 2 Features used for classification

From: Detecting sequence dependent transcriptional pauses from RNA and protein number time series

#

Feature

Description

Data

1

m(r xx ;R M )

mean autocorrelation function

R M

2

s(r xx ;R M )

standard deviation of autocorrelation function

R M

3

m(r xx ;P M )

mean autocorrelation function

P M

4

s(r xx ;P M )

standard deviation of autocorrelation function

P M

5

m(r xy ;R M ,P M )

mean cross-correlation function

R M and P M

6

s(r xy ;R M ,P M )

standard deviation of cross-correlation function

R M and P M

7

m(r xy ;P M ,E M )

mean cross-correlation function

P M and E M

8

s(r xy ;P M ,E M )

standard deviation of cross-correlation function

P M and E M

9

m(d(R M ))

mean decay time

R M

10

s(d(R M ))

standard deviation of decay time

R M

  1. Summary of the 10 variables we use to define a feature vector for a model M.