1 al design analysis was carried out to reduce the number of experiments.

2  data when the number of TFs is greater than the number of experiments.

3 ed theories about population coding and keep the number of experiments and animals to a minimum.

4 nidine when applied topically but because of the number of experiments carried out a comparison betwe

5 ry network that could explain the data, when the number of experiments does not allow identification

6 eening all combinations is difficult because the number of experiments grows exponentially with the n

7 ue to high information content while keeping the number of experiments low.

8  required experimental sampling and estimate the number of experiments needed to "complete" a particu

9 nt, active learning has been shown to reduce the number of experiments needed to obtain high-confiden

10 rs were investigated using FFD which reduced the number of experiments performed by identifying 720 k

11  catalytic rate laws from only a fraction of the number of experiments required in classical kinetic

12                       Next, it is shown that the number of experiments required to characterize a com

13 d data and results in substantial savings in the number of experiments required to make accurate drug

14                    Both parameters determine the number of experiments required to obtain meaningful

15  discovering useful cocrystals and decreases the number of experiments that are needed by selecting A

16  laboratory techniques has greatly increased the number of experiments that can be carried out in the

17 the analysis is thus roughly proportional to the number of experiments, underscoring the need for min