Gene perturbation and intervention in probabilistic Boolean networks

By Ilya Shmulevich, Edward R. Dougherty, Wei Zhang. Bioinform., 2002

308 citations recorded by the source corpus.

Subfields: Modeling and Simulation, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2244e3eb78899c1a200cc1d0b7b098df19e09479

How researchers see this paper

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

In Modeling and Simulation

1. A. Y. Mitrophanov
2. Edward R. Dougherty
3. Ilya Shmulevich
4. Wei Zhang

In Molecular Biology

1. A. Y. Mitrophanov
2. Ilya Shmulevich
3. Wei Zhang
4. Edward R. Dougherty
5. Ruth Nussinov
6. Peter Csermely
7. Huba J. M. Kiss
8. Tamás Korcsmáros

Citations in the corpus

• Sensitivity and convergence of uniformly ergodic Markov chains (2005, methodology): “As a recent example, we mention the application of perturbation bounds for Markov chains in bioinformatics [27].”
• Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “Thesemodels often incorporate activating, inhibiting, or conditional edges, too (Huang, 2001; Shmulevich et al., 2002; Gong & Zhang, 2007; Abdi et al., 2008; Azuaje et al., 2010; Saadatpour et al., 2011; Wang & Albert, 2011; Garg et al., 2012).”
• From Boolean to probabilistic Boolean networks as models of genetic regulatory networks (2002, methodology): “teresting implication of the result given in [96] is that the steady-state probabilities of those states of the network to”