Our recently introduced structure preparation tool SPORES [1] used a rule based method to generate a standard protonation for each ligand molecule and afterwards generated different protonation states in a combinatorial way by adding and removing single hydrogen atoms belonging to predefined functional groups.
The binary heap consistently took significantly less time than the treap-based methods to generate networks of several different sizes.
Bleakley et al. proposed Bipartite Local Model (BLM), which integrated the ligand-based and target-based methods to generate a comprehensive prediction [ 11].
Since it has been shown that recombinant Oct4 fused to a cationic fusion tag can drive generation of iPSCs, our finding might contribute to further development of protein-based methods to generate iPSCs.
In this paper, we describe our approach, which applies a subsectional-bases method to generate a boundary division, representing the shape and behaviour of the Wien filter precisely.
In this section, we propose two graph partition algorithms, K- nearest neighbor ( KNN) method and Edge betweenness based (EBB) method, to generate a generalized social network G' for sharing purpose.
Weichao Wang et al. design a hash based defending method to generate node behavioral proofs which involve the data traffic information within the routing path.
We first applied a local variability based sampling method to generate reference samples that have sampling distances varying spatially and temporally to monitor a soil erosion relevant cover factor for an installation, Fort Riley, USA.
A statistically significant difference in diagnostic performance was observed between dataset 2A-3 that used the MTRC-3 with a linear isothermal amplification method and dataset 3C-3 that used the MTRC-3 with the T7 RNA polymerase based amplification method to generate target for hybridization to arrays (Table 3).
The MGA uses the sequential-search based efficient generation (SSEG) method to generate an initial population to determine the most efficient mutation points.
