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The model checking method has been long since established as an important tool for modelling and reverse engineering of biological systems.
An improved version of this model checking method requiring less input parameters is described in [ 54].
In this work, we will extend our previous synchronous verification technique and propose an asynchronous model checking method to formally analyze the ER-Golgi-regulated signaling pathways.
Using the model checking method, we verified several Alzheimer's disease and cancer-related properties, and also identified important proteins (NFκB, ATF4, ASK1 and TRAF2) in the ER-Golgi network, which might be responsible for the pathogenesis of cancer and AD.
Compared with [ 6, 7], the oscillation phenomenon is parameter-independent in our discrete value model using the Symbolic Model Checking method.
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Using the synchronous and asynchronous model checking methods, we can test this type of dynamic behaviors in the ER-Golgi network through verifying the following CTL formulas.
The algorithms provided in the original papers describing the model checking methods (see Table 2) were employed for all approaches except frequentist statistical.
Then, we propose and apply both asynchronous and synchronous model checking methods, which extend our previous verification technique, to automatically and formally analyze the ER-Golgi-regulated signaling pathways in the cell cycle progression through verifying some computation tree temporal logic formulas.
We present a temporal logic and an associated model-checking method that attempt to fulfill these criteria.
This chapter presents a model checking with abstraction method that mainly checks synchronization properties for concurrent processes.
In this contribution the combination of Signal Interpreted Petri Nets (SIPN) as formal model and symbolic model checking as verification method is proposed.
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