Suppose we are given a set of M motifs ℳ m, m=1,…, M, which may either come from a database or from a de novo motif detection method.
From the full set of sequence reads, we infer a set of M SNPs, indexed by j = 1, …, M.
We then propose an algorithm to find a set of M test conditions that suffices.
Let us consider a set of M time-varying poles, {ξ k [ m], k = 1, …, M}.
The sampler provides all samples in the first segment of a set of M 1 segments.
Let ({mathscr {A}}) denote a set of (m in mathbb {N}) symbols called the alphabet.
Let (S) be a set of elements to be ranked by a set of (m) rankers.
On the network side, either each eNodeB or the HSS stores a set of M secret spreading sequences.
I − the inverted index including a set of m posting lists I = {I(w i )}, i = 1, 2, ⋯ m.
Consider a set of M homogeneous populations labeled (alpha=1,ldots,M), with ({mathcal{N}}) neurons in each population.
Let us assume that a set of m states, namely, s m ≡ sk,1,…,sk,m, are observed.
