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By using a seed crystal, the high-temperature hexagonal close packed α-phase can be correctly oriented so that an aligned lamellar TiAl/Ti3Al microstructure results from the subsequent solid-state transformations upon cooling.
Some MD-based modelings avoid this problem by using a seed or template protein structure obtained under similar experimental conditions.
By using a seed network to query multiple retinal gene expression datasets we were able to identify candidate genes for further study related to rod photoreceptor development.
Reads were aligned by using a seed length of 50 bp, and only the single best alignment per read with up to two mismatches was reported in the SAM file.
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By using a seeding-growth technique, the relative monodispersed CdSe/ZnS NCs were prepared.
One of us has demonstrated previous success identifying gene candidates in development of rod photoreceptors by using a seed-network-based heuristic to query high throughput data [7], and this success motivated our efforts to further develop strategies to identify effective seed networks to query large datasets.
The sensory-motor ICN was first demonstrated in fMRI by using a seed-based methodology [ 3], as was the prominent ICN known as the default mode network (DMN) [ 14] (see section B, 'Task-free functional magnetic resonance imaging Alzheimer's disease studies').
The use of seeds can be a highly effective heuristic, and BWA can run faster by using a seeding mode that allows a certain number of mismatches in the initial part of the short read.
The first algorithm, Best Topic Selection (BTS), minimizes online processing by simply using a seed set for one of the constituent topics.
Therefore, we speculate that the effect of seed thickness can be ignored by using a thick seed layer.
In addition, highly crystalline of FER@FER, which was synthesized by using a FER seed, showed a higher DME conversion to MA and stability due to the abundant presence of Bronsted acid sites with less defect sites.
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