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CONSENSE program was used for computing the consensus tree.
The first 25% of the trees obtained in the analysis were discarded as burn-in before computing the consensus tree.
One million generation with 4 chains were run for Bayesian analysis and the trees sampled prior to reaching convergence were discarded (as burnin) before computing the consensus tree and posterior probabilities.
The motif was identified by overlaying the binding sites of Zfp57, Kap1 and Setdb1, identified by separate ChIP-seq experiments, and computing the consensus sequence over all sites occupied by all three proteins.
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Finally, computing the consensuses of the clusters can be done in O(n k *) time.
We compute the consensus, weighted graphs for two scoring metrics.
The remaining trees were used to compute the consensus tree.
We first computed the consensus of our 24,155 protease sequences.
Then, we compute the consensus matrix, C ¯, defined as the average over all connectivity matrices.
We computed the consensus structure of RPS17B and RPS6B introns using Alifold [ 26].
For the (1) full consensus sequences, we computed the consensus residue at each sequence position, and for the (2) partial consensus, we computed the consensus in a constrained way, e.g. only for the more informative positions.
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