Sentence examples for the interactions stated from inspiring English sources
In this paper we have assumed that the interactions stated in the literature are correct, but if for example, a compound is reported as interacting at point 3 in Figure 2, it is possible that its actual effect occurs at any point from 1 to 3. In addition, it is entirely possible that molecular interactions may occur at multiple points in the pathway.
Our aim in this work is to recover as many of the biomolecular interactions stated in the texts as possible, so we extend the criteria for what is considered a named entity and an event.
In this syllogism x → y and y → z are known interactions stated in the literature.
The seeded BN approach that we describe here models interactions between gene expression states and these may not be identical to the interaction states of the corresponding proteins.
(H ) Comparison of the interaction states of the four protein pairs shown in (G ) in focal adhesions with their physical associations near and far from focal adhesions.
A simple example of this algorithm is illustrated in Supplementary Figure S4 We now describe an algorithm that can use the counts derived via the algorithm in Section 3.4 to estimate probabilities for network history events (i.e. the interaction state or relative duplication order of ancestral proteins) based on how often they occur in the ensemble of near-optimal solutions.
This paper examines the interactions between state-led land reform, agrarian structures, and deforestation in the Brazilian Amazon.
For each subsystem, a local estimator is designed to estimate the interactions and states of the subsystem, using only the local output measurements.
This article focuses on the interactions between state and community mechanisms in the design and delivery of a titling program and a land market reform in rural Mexico.
In literature-based discovery we must avoid the inference of interactions already stated in the literature.
Each model controlled for the state variable and the interaction between state and time, in order to accommodate expected heterogeneity in the data.
