# t ∈ [0, 1]: t≈0 shifts mass toward low indices, t≈1 toward high indices. # n: number of probabilities returned (beta-binomial with N = n-1 trials). # The sigmoid maps t ∈ [0,1] so that t=0 → m≈0.007 ...
Dynamic programming algorithms are a good place to start understanding what's really going on inside computational biology software. The heart of many well-known programs is a dynamic programming ...
1) Use dp[i][j] = iCj. 2) Base cases: dp[i][0]=dp[i][i]=1. 3) For others, dp[i][j]=dp[i-1][j-1]+dp[i-1][j]. 4) Build row by row up to n. 5) This is Pascal's triangle ...
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