### Table 1. Similarities Between Biological and Computer Systems

2001

"... In PAGE 2: ... The major difference in the targets between the immune system and an ISS is: the immune system treats as an enemy any foreign entity within the organism, while an ISS must recognize and treat as an enemy any illegitimate entry or software. Table1 shows some of the similarities between the two systems. A number of mathematical models of individual behavior of defensive cells utilizing methods of statistics, discrete mathematics, and numerical simulation, have been successfully implemented.... ..."

Cited by 1

### Table 4.2 Software for Modeling and Simulation of Biological Systems

### Table 4.2 Software for Modeling and Simulation of Biological Systems

### Table 1: Stochastic automata for L (X = p 2 E)

1997

"... In PAGE 9: ... To associate a stochastic automaton to a given term in the language, we need to de ne the di erent parts of the stochastic automaton. We start by de ning predicates and - as the least relations satisfying rules in Table1 . However, not all the processes can have a straightforward stochastic automaton as a semantic interpretation.... In PAGE 9: ...The second occurrence of xG is intended to be bound to the outermost clock setting as shown by the grey arrow. Using the rules in Table1 , the following stochastic automaton would be obtained b; fxG; yHg a; ; xG xG yH... In PAGE 13: ... We use the notion of adversaries or schedulers [29, 24] to resolve non-deterministic choices. Since parallel composition of stochastic automata can be easily de ned (actually, it is de ned just like for the process algebra, see Table1 ), the simulation algorithm can compose the complete stochastic automaton on the y, which reduces the state space explosion problem. Although (probabilistic) adversaries allow to obtain a complete probabilistic nal model, the inclusion of them as a new ingredient is not that appealing since it would require an additional e ort when modelling systems.... ..."

Cited by 13

### Table 1: Stochastic automata for L (X = p 2 E)

1997

"... In PAGE 8: ... To associate a stochastic automaton to a given term in the language, we need to de ne the di erent parts of the stochastic automaton. We start by de ning predicates and - as the least relations satisfying rules in Table1 . However, not all the processes can have a straightforward stochastic automaton as a semantic interpretation, as we see as follows.... In PAGE 8: ... Consider the process p1 fjxGjg (a; fxGg7!(fjxG; yHjg fyHg7!b; stop)) (2) The second occurrence of xG is intended to be bound to the outermost clock setting as shown by the grey arrow. Using the rules in Table1 , the following stochastic automaton would be obtained b; fxG; yHg a; ; xG xG yH In this sense, xG would be captured by the innermost clock setting as shown by the black arrow in formula (2). Therefore, we consider that clocks are di erent if they are set in di erent places, although they may have the same name.... In PAGE 12: ... We use the notion of adversaries or schedulers [29, 24] to resolve non-deterministic choices. Since parallel composition of stochastic automata can be easily de ned (actually, it is de ned just like for the process algebra, see Table1 ), the simulation algorithm can compose the complete stochastic automaton on the y, which reduces the state space explosion problem. Although (probabilistic) adversaries allow to obtain a complete probabilistic nal model, the inclusion of them as a new ingredient is not that appealing since it would require an additional e ort when modelling systems.... ..."

Cited by 13

### Table 1 Discrete-event simulation algorithm for stochastic event structures.

"... In PAGE 11: ... It is not di cult to check that the above described discrete-event system for stochastic event structure is a time-homogeneous GSMP. The complete simulation algorithm for stochastic event structure hE;A;Ri with E = (E;#;7!;l) is presented in Table1 . For random variable U with distribution FU let FU( ) denote a sample of U; output state si = (Ei;Ri;Hi), for i gt; 0.... ..."

### Table 4: Comparison of biological and broadcast language terminology

### Table 1. The syntax of the intermediate language (IL).

1998

Cited by 23

### Table 1. The syntax of the intermediate language (IL).

1998

Cited by 23

### Table 7. Properties of Certain Intermediate Languages Summarised

"... In PAGE 7: ... In the sequel, a number of properties of these languages will be pointed out and followed by a discussion on their prevalence among the quintet under consideration. A summary of these results is collected in Table7 . However, certain properties shared/lacked by all formats are not mentioned for space reasons but subsequently discussed in Section 3.... In PAGE 9: ... The remaining two formats are easy to extend by new syntax due to flexibility of their grammars. Interestingly, none of the formats under consideration has all of properties sum- marised in Table7 . The BCSAT format appears to be closest to having them all.... In PAGE 12: ...23 The five items above cover most of the aspects raised in the analysis carried out in Section 3. However, one aspect of the format remains open in view of Table7 , i.e.... ..."