Sentence examples for models gene regulation from inspiring English sources

Therefore, for each cell type we compared two models: gene regulation as a function of both TF ChIP and input signal, and gene regulation as a function of input signal alone.

Subsequent scaling divides the centered time series by its maximum absolute value, which leads to gene-wise scaled data varying within -1 and 1. Network inference was performed using the NetGenerator tool, which models gene regulation by a system of ordinary differential equations (Equation 1).

This is necessary as the modeling concept of TILAR-based algorithms allows to model gene regulation exclusively via TFs and not directly between the genes.

By analyzing the relationship between the locations of TF binding motifs and their adjacent genes, it is feasible to model gene regulation.

This involves modeling gene regulation mathematically.

There are three main reasons we tend to model gene regulation with an equilibrium framework.

Bayesian Networks (BN) learning approach is a well-established method of modelling gene regulation and interactions between gene regulatory motifs, starting from gene expression data [ 13] or gene expression and genomic sequence data [ 14- 20].

The methodology is suited to the bottom-up approach to modeling gene regulation networks, where the complete network is divided into loosely connected subnetworks, each containing only a few genes.

This may manifest as Boolean or discrete values, and is primarily employed in modeling gene regulation, signaling pathways, logical/Boolean networks (Schmulevich et al., 2002), and Petri nets (Breitling et al., 2008).

There are signs that this is starting to happen: the sixth edition of Molecular Biology of the Cell, for example, includes examples where ordinary differential equations are used to model gene regulation and to explain switch-like and oscillatory dynamics.

ChIP-seq capTFres TF binding as it happens in vivo, so using ChIP-seq data alone or as a basis in more integrative methods for modeling gene regulation will result in context-specific predictions [ 17, 18].