The PhD project is to formulate a rule-based approach to computational systems biology that combines the ability to form complexes (such as protein complexes) with multi-level dynamic compartments (as in, e.g., viral infection processes). Rule-based systems start with the usual notation for chemical reactions, such as
2 H
2
+ O
2
2 H
2
O but note the addition of a stochastic rate k
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For complexes, we might write a rule such as:
A u
(Site
1
: open) , B (Site
2
: open) , k
−→ A u
(Site
1
: x ) , B (Site
2
: x ) in which an unphosphorylated protein A and a protein B with specified open sites bind together at these sites. For mutlilevel processes, we might write a rule such as:
Virus , Cell u
( X ) k
−→ Cell i
(gen , 80V
1
, 40V
2
, X ) in which a virus infects an uninfected cell. The first rule is written in a variant of Danos et al’s κ formalism; the second is written in a stochastic multilevel rewriting formalism, here called λ , developed by N. Oury and myself.
Combining these approaches one would envisage writing rules like:
Cell(s : x, n : open | X, Sig) , Cell(s : open , n : z | Y ) k
−→ Cell(s : x, n : y | X, Sig) , Cell(s : y, n : z | Y ) in which two cells, each with “south” and “north” sites (one with an open north site, one with an open south site) may join at those sites when the former cell has received a signal
“Sig.” Let’s call such a rule-based approach κλ .
The project would:
(1) Develop κλ theory, particularly combining term-based and graph-theoretic views.
(2) Provide an experimental implementation (encouragingly the current implementations of κ and λ have common features).
(3) Test it out on interesting biological examples, e.g., in which cells may form tissues and have internal pathways guiding tissue formation by intercellular signalling.
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