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Table 3 Runtime of our implementation

From: TMRS: an algorithm for computing the time to the most recent substitution event from a multiple alignment column

Computation

Datasize

Runtime

Train, gradient (1 iteration)

100 K columns

4.6 min

Train, total (300 iterations)

100 K columns

23 h

\(t_{\text {MRS}}\), \(\sigma\), q

1 column

\(7.3\times 10^{-4}\) s

\(t_{\text {MRS}}\), \(\sigma\), q

1 G columns

204 h

  1. We show runtimes of our implementation. We used 100 species vertebrate multiple alignments for the measurements. For training data, we used a sampled alignment with 100 K columns from 4d sites. As for the computation of \(t_{\text {MRS}}\), \(\sigma\), and q, we used the sampled alignments from 3\('\)UTR sequences which have 2,034,681 total alignment columns, and scaled the runtime for each Datasize
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Algorithms for Molecular Biology

ISSN: 1748-7188