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Whereas the original RosettaLigand method performed a full sampling of torsional degrees of freedom in the internal ligands and protein side-chains, we made modifications to enable the fast run time required by the screening method.
As shown in Table 1, the proposed method performed a lower median absolute relative bias (ABS range 1.7% ~ 8.5%) than those solely based on daily confirmed cases (ABS range 4.7% ~ 67.7%) between July 6 and December 31.
The MCODE method performed a typical seed-growth-style-clustering algorithm, which ranks the subnetworks with clusters according to the average number of connections per protein in the complex as node score.
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The MLST method performed an efficient discrimination of 17 strains and helps to understand the population structure of this bacterium.
The proposed method performs a pair-wise KFDA on normal and fault data.
This method performs a poll step iteratively to search a better solution and updates parameters to adjust its learning rate.
Then, the Chang-Cooper method performs a kind of θ-finite difference approximation of p / M, see [31] for details.
The core method performs a frame by frame analysis, selecting the most likely combination of fundamental frequencies at each instant.
The second step of the method performs a qualitative product analysis in order to eliminate the worst assembly sequences.
Simulation results indicate that the proposed method performs a good time response, and robustness is obtained effectively.
First, our method performs a series of local solves to survey the behavior of the local error function.
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