Modelling and analysis of gene regulatory networks

By Guy Karlebach, Ron Shamir. Nature reviews. Molecular cell biology, 2008

1,300 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ccf43cc6cc36420341f9192de13526f13fa8c238

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

Artificial intelligence in cancer target identification and drug discovery (2022, background): “…targets and discovery of novel drugs for cancer from molecular networks such as protein-protein interaction networks 75 , gene regulatory networks 93 , metabolic networks 94 , and drug-drug interaction networks 95 . analyze non-ordered or non-Euclidean data in biological networks, which can…”
Hierarchical Network Structure Promotes Dynamical Robustness (2014, background): “The top row represents a chemical reaction network (CRN) [39], a gene regulatory network (GRN) [40], and an ecological regulatory network (ERN) [41] in terms of the graphical methods specific to each field mapped into the interaction graph, which provides a unified representation for networks across”
Output tracking control of Boolean control networks with impulsive effects (2018, neutral): “A direct calculation gives x(1) = Γ1x(0)x̂(0), x(2) = Γ1x(1)x̂(1) = Γ(2)1(I2n+n1 ⊗ L3)(I2n ⊗ Mr,2n1 )x(0)x̂(0) ∶= Γ2x(0)x̂(0), ⋮”
The evolutionary origins of modularity (2012, neutral): “(g) Network model details Our model of a network is a standard, basic one used in machine learning [40], systems biology [2,13,14,43] and computational neuroscience [44].”
Universality in network dynamics (2013, neutral): “…of infection [23–25], (b) biochemical dynamics ( ), in which x i represents the concentration of a reactant [26–29] (c) birth-death processes ( ) [30–32], in which x i represents the population at site i and (d) regulatory dynamics ( ) in which x i is the expression level of a gene [33, 34].”
Network neuroscience (2017, methodology): “Similar modeling and simulation approaches are applied to protein interaction and genetic regulatory networks 76 , can capture the translation of genotype to phenotype in whole cells 77 , and have become important tools in studies of social dynamics and collective behavior 78 .”
Big Data Analytics in Healthcare (2015, methodology): “Boolean networks are extremely useful when amount of quantitative data is small [135, 153] but yield high number of false positives (i.e., when a given condition is satisfied while actually that is not the case) that may be reduced by using prior knowledge [176, 177].”
Network resilience (2020, methodology): “The dynamics in gene regulatory networks can be modelled as Michaelis-Menten equations [784, 785]”