Sentence examples for multiple regulatory interactions from inspiring English sources

It should be kept in mind, though, that peripheral tolerance in vertebrates is an active and complex process that fine-tunes the immune response through multiple regulatory interactions.

It occurs in many biological systems, including two oscillators of cell division and the circadian phase or within a cell cycle oscillator through multiple regulatory interactions.

Mcm2-7 is a structurally and functionally complex replication factor with a rich binding surface that directs multiple regulatory interactions of cancer significance, including those required for both Rb/E2F signaling as well as DNA replication.

Recent advances in translational research studies have highlighted the complexity of ER signaling, including differential roles for the ERα and ERβ subtypes [ 6], and multiple regulatory interactions between steroid hormone, growth factor, and other tyrosine kinase signaling pathways [ 7– 10].

Intuition alone cannot grasp the effects of multiple regulatory interactions and thus mathematical models are particularly well suited for unraveling the implications of the underlying nonlinear interactions [ 10- 14].

We represent the combinatorial relationship of multiple regulatory interactions converging on a node v by a Boolean rule (see Methods) which can be uniquely written in the following disjunctive normal form: where u ij are regulators of node v. Usually the Boolean rules for each node will need to be constructed individually on the basis of the existing biological evidence.

It is unlikely that the systemic differential-targeting of functions we see across our panel of transcription factors in Figure  6A actually corresponds to multiple strong regulatory interactions from every one of them.

Multiple-TF regulatory interactions were inferred with a new association mining algorithm.

For an illustrative example, there are 40 possible multiple-TF regulatory interactions in the regulatory module shown in Figure 1b.

In order to identify these multiple-TF regulatory interactions, a new association rule mining approach has been developed.

A synthetic transcriptional regulatory network was generated to evaluate the performance of mTRIM in detecting high-order multiple-TF regulatory interactions (see Figure 4).