Because it is extreme slow to find the best PrSM with two PTMs by searching a spectrum against a large random protein database with 10 proteins, the evaluation method based on conditional spectral probabilities was not used.
We balanced the trial arms for key characteristics by calculating an imbalance statistic for a large random sample of possible allocation sequences.
Sequencing DNA molecules selected from a large random population by repetitive selection (SELEX) and PCR-amplification, based on increased archaeal histone-DNA affinity, revealed that DNA molecules preferentially assembled into archaeal nucleosomes in vitro had sequences that conformed to the eukaryotic nucleosome positioning code [ 12].
The only way of addressing these issues is by screening a large random sample of the population, with matched maternal samples, to determine whether the detected mutations are de novo or inherited.
A cross-sectional study was conducted between May 2009 and October 2010, recruiting households and individuals through postal and online questionnaires, supported by a large random-address mailshot and a modest online and media promotion [30, 31].
It was shown previously that flux estimates using the vDEC method are characterized by a larger random uncertainty compared to the true EC, but are unbiased (Hörtnagl et al., 2010).
The results above were obtained by a large anonymous random, postal survey carried out by the Veterinary Faculty (University of Liège, ULg and University of Namur) after a awareness campaign had been conducted to explain the clinic pattern of BTV-8 infection (the first outbreaks were followed by a multidisciplinary team of the ULg).
We find that the algorithms considered obtain performance gains similar to the optimal ones found by complete enumeration or by large random searches but in a tiny fraction of the computation time.
Failure events defined by a large number of random variables are used to characterize the reliability measures.
The external validity of the articles were scored ranging from 1 (very strong external validity supported by a large study population, random sample, and explicit analysis of context and intervention factors for which generalization is possible) to 4 (weaker external validity based on weak or selective reference population, and weak intervention and context reference).
However, these subgroup analyses were affected by large random variation, so we could not distinguish between different models.
