Sentence examples for true regulation from inspiring English sources

In this model, it is recognized that extensive upstream sequence conservation makes false positive predictions more likely and, consequently, the probability of true regulation needs to be downweighted.

Although we suspect the former to be true, regulation of mTOR through these pathways has proven to be quite complex and the answer may not prove to be straightforward.

The high CV error in this case, indicates that a lot of true regulation is missed.

This also reflects that in real biological processes, time lag regulation might better describe the true regulation between genes.

Consider a network in which every gene can have several alternative regulation functions, each associated with a probability that it is the true regulation.

These can handle abundant expression data, but often fail to distinguish true regulation from co-expression (Amit et al., 2009; Kim et al., 2009; Segal et al., 2003;).

The events corresponding to the true regulations of different genes are assumed to be independent.

Initially, the increase in gene-to-gene signal strength had a beneficial effect on performance because stronger signals aided in distinguishing true regulations from noise.

Generally, it is difficult to estimate true regulations in a highly correlated data set, since the Markov equivalence classes of a directed network cannot be identified uniquely (Uhler et al. 2013).

The set of all candidate regulations is therefore E = (t, g ), g ∈ G, t ∈ T g, and the GRN inference problem is to identify a subset of true regulations among E. For that purpose, we assume we have gene expression measurements for all genes G in n experimental conditions.

In other words, we only focus on finding a good ranking of the candidate regulations E, by decreasing score, such that true regulations tend to be at the top of the list; we let the user control the level of false positive and false negative predictions he can accept.