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Following this goal, the Persistent Phylogeny model and the related tree reconstruction problem (the PPP problem) have been recently introduced: this model allows only one back mutation for each character.
Mutation: for each g∈{1,2,…,G−1}, we randomly change part of (mathbf {S}^{n}_{G}).
Selection for mutation For each solution of (N_{mathrm{pop}},) generate a random number r from the interval (0, 1).
The probabilities of crossover and mutation for each generation are adaptively determined, which can overcome the premature convergence and the slow convergence speed in later evolutionary processes.
The steps for this purpose are presented below: (i) Selection for mutation For each solution of (N_{mathrm{pop}},) generate a random number r from the interval (0, 1).
As outlined below, the structurally similar residue glutamine (Q) was used as a control mutation for each position.
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(Supplementary file 2 lists all the mutations for each mutated episome).
They estimate a separate background mutation rate for each mutation type by multiplying relative frequencies of each mutation type by the background rate ρ N.
We estimated the cancer risk for first-degree relatives of mutation carriers for all mutations and for each mutation separately, using Kaplan Meier survival analysis.
In the next step, GWAMAR computes binary mutation profiles for each mutation profile.
Specific mutations for each cancer as well as the percentage of mutated BRCA1 DNA (m%), NM_score, and ER status for each cancer is shown in Additional file 5.
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