Sentence examples for seed optimization from inspiring English sources

In this article we examine the hardness of the seed optimization problem by a polynomial time reduction from the optimal Golomb ruler design problem, which is a well-known difficult (but not NP-hard) problem in combinatorial design.

For some simple distributions of the similarities, the seed optimization problem was proved to be not NP-hard.

Following seeding optimization, we compared the utility of (i) KO-DMEM plus KO-SR, supplemented with LIF and (ii) GMEM supplemented with serum and LIF to support expansion of pluripotent mESCs on three types of microcarrier.

Following seeding optimization, single cell suspensions of mESC or a suspension containing small clusters of hESCs were seeded onto microcarriers at a density of 6 × 10/mL with intermittent stirring of 10 min off, 2 min on at 15 rpm for the first 24 h.

Modelling dry conditioning of seeds and optimization of operation conditions were performed using Response Surface Methodology with a total of 11 dry conditioning experiments, following a central composite rotatable design as a function of temperature (52 108 °C) and time (8 92 min).

It may be beneficial to perform a seeding density optimization study such as the one presented here when applying the model to new stem cell lines, centered around 30,000 cells/cm.

Once the optimal motif was identified, it was used as a seed for the optimization procedure.

BMECs displayed the highest TEER (>2,000 Ω × cm) within this same range of initial seeding densities, although optimization of the BMEC purification method could minimize the seeding density dependence for some lines.

IncaRNAtion applies a two stage-optimization approach that first produces GC-optimized seed sequences that are subsequently optimized towards the target structure by RNAinverse.

Results of studies demonstrated effectively that suitable processing is necessary to elicit the enhanced electrical properties of PMN PT thin films, such as introduction of suitable seeding layers and optimization of synthesis conditions.

Finally, contigs are threading from the seeds graph after optimization for repeats and sequencing errors.