Accordingly, we sorted the pairs using the degree of sequence similarity between the genes and the corresponding RNAi clones (see Methods for details).
MI-GRAAl was run using the degree, signature similarity and sequence similarity.
In other words, quantiles can be used to find the maxima of the degree sequence with certain probability.
Using Eq. 6, we can approximate the degree sequence by a random walk on degree space with the following transition kernel: f_{text{RW}}(d_{t+1}|d_{t}) = frac{mathrm{E}[D] f(d_{t},d_{t+1})}{d_{t} f_{d}(d_{t})}, (10).
We take {X i } as the degree sequence and use RW, PR, and RWJ as the sampling techniques.
The degree sequence, denote by D S ( G ), is a sequence of degrees of vertices of a graph G.
We use r = 0.45 and choose a generated network that has 4625 nodes and best fits the degree sequences of the original yeast PIN (with 4625 nodes).
Then we expanded the degree sequences into node frequency sequences.
Draw squares using the Fibonacci sequence.
It uses degree sequence for finding largest possible clique size.
