The phrase "large-scale regulatory" is grammatically correct and commonly used in written English.
It refers to the regulation of a large or broad area or industry. It can be used in various contexts, such as business, government, and economics. Example: The government implemented a new large-scale regulatory policy to address the environmental concerns of the public.
Global studies of gene regulation and chromatin state in human cells are revealing the large-scale regulatory architecture of the genome.
Large-scale regulatory network reconstructions can be converted to in silico models that allow systematic analysis of network behavior in response to changes in environmental conditions.
"In addition, against the backdrop of large-scale regulatory change already underway, the sector has to navigate the loss of regulatory uncertainty as the UK negotiates new trade relationships with the European Union".
In many European countries [3], including Germany (E-Energy projects [2]), large-scale regulatory experiments are carried out.
In Qualcomm's countersuit, filed last month, the company denied the charges and brought a number of its own accusations, including that Apple mounted a large-scale regulatory attack against the company with the help of companies like Samsung.
Unlike budding yeast, no large-scale regulatory network has been constructed for fission yeast.
The software takes advantage of the extensive BioASP functionality in manipulating influence graphs, allowing for the modelling of large scale regulatory networks and dealing with inconsistency with extensive repair capabilities.
On the other hand, BioASP only calculates predictions under repair that hold true under all repair sets (i.e. not all possible), however it is capable of dealing problems of much larger size, rendering it ideal for modelling large scale regulatory networks.
Nevertheless, confronting experimental data with a regulatory network entails many difficulties, such as the incomplete state-of-art of regulatory knowledge, the large-scale of regulatory models, heterogeneity in the available data and the sometimes violated assumption that mRNA expression is correlated to protein activity.
We have pioneered methods to predict, dissect, and control large-scale gene regulatory programs; these methods have provided insights into human development, cancer, and aging.
In this paper, we describe some of the most commonly used multivariate inference techniques for large-scale gene regulatory network reconstruction.
