Computational protocol: Boolean Model of Yeast Apoptosis as a Tool to Study Yeast and Human Apoptotic Regulations

Similar protocols

Protocol publication

[…] In order to convert the schematic network into Boolean model we used SQUAD (Mendoza and Xenarios, ), a user friendly graphical software which is suitable for modeling signaling network where kinetic reactions are not available. Simulation in SQUAD consists of three steps: (1) the network is first loaded from the SBML file. Components of the network are presented as nodes and value of each node represents the state of that node. SQUAD converts the network to discrete dynamic model. Using Boolean algorithms all steady sates in network are calculated. (2) network is converted to a continues dynamic model generating sets of ordinary differential equations (ODEs) and steady states achieved in pervious step. (3) SQUAD allows perturbation in order to understand the role of each node within the network.Using Reduced Order Binary Decision Diagram (ROBDD), it is possible to calculate steady states (Di Cara et al., ). ROBDD is a memory efficient data structure which is widely used in electronic field and has been proven to work for large binary networks. Moreover, ROBDD computes steady states for large networks (n > 50) in matter of seconds. Another advantage of this algorithm is its ability to identify the cyclic steady states. These oscillating states are reachable when system identifies a cyclic pattern instead of one single state.In the first step, schematic network is supplied to SQUAD resulting in a discrete network, generating a set of either cyclic or single steady states. These steady states are then used to convert discrete model to continues. Given all calculated steady states or cycles we examined all possible outcomes for each input. Depending on the desire form of output, discrete to continuous conversion can be carried out either as a complete or progressive mode. Our simulations are performed in the complete mode since cell undergoing apoptosis should die after certain time and it is expected to maintain a constant level of apoptosis or survival (in case when apoptosis is not activated) at the end of each run. As an opposite to complete mode, the progressive model allows the user to stop the simulation at any time even before reaching the steady states. [...] Reconstructing Boolean model of yeast apoptosis from qualitative knowledge never gives details about concentration of molecules in different time points. For this purpose the discrete Boolean model is transformed to continuous model using Odefy. Odefy uses the multivariate polynomial interpolation in order to transform the logical rules into sets of ODEs. Yeast apoptosis Boolean model is converted to continuous model using Hill Cube and normalized Hill Cube where the Hill function is normalized to the unit interval. Behavior of biochemical reactions can be seen as a sigmoid Hill function represented as f(x¯¯)=x¯¯n∕(x¯¯n+kn). Where, n is a Hill coefficient and determines the slope of the curve and is a measurement of cooperativity of the interactions, and parameter k corresponds to values 1 and 0 in the Boolean model in the following manner: threshold value above given k in Boolean model is considered as 1 (on state) and below as 0 (off state). […]

Pipeline specifications

Software tools SQUAD, Odefy
Application Mathematical modeling
Organisms Saccharomyces cerevisiae, Homo sapiens
Diseases Neoplasms, Neurodegenerative Diseases