RaTrav

BACKGROUND: The concept of mean first-passage times (MFPTs) occupies an important
place in the theory of stochastic processes, with the methods of their
calculation being equally important in theoretical physics, chemistry and
biology. We present here a software tool designed to support computational
biology studies where Markovian dynamics takes place and MFPTs between initial
and single or multiple final states in network-like systems are used. Two methods
are made available for which their efficiency is strongly dependent on the
topology of the defined network: the combinatorial Hill technique and the Monte
Carlo simulation method. RESULTS: After a brief introduction to RaTrav, we
highlight the utility of MFPT calculations by providing two examples (accompanied
by Additional file 1) where they are deemed to be of importance: analysis of a
protein-protein docking funnel and interpretation of the free energy transduction
between two coupled enzymatic reactions controlled by the dynamics of transition
between enzyme conformational states. CONCLUSIONS: RaTrav is a versatile and easy
to use software tool for calculating MFPTs across biochemical networks. The user
simply prepares a text file with the structure of a given network, along with
some additional basic parameters such as transition probabilities, waiting
probabilities (if any) and local times (weights of edges), which define
explicitly the stochastic dynamics on the network. The RaTrav tool can then be
applied in order to compute desired MFPTs. For the provided examples, we were
able to find the favourable binding path within a protein-protein docking funnel
and to calculate the degree of coupling for two chemical reactions catalysed
simultaneously by the same protein enzyme. However, the list of possible
applications is much wider.

RaTrav: a tool for calculating mean first-passage times on biochemical networks.

RaTrav is a tool to compute  mean first-passage times (MFPTs) across biochemical pathways. The RaTrav algorithm provides two methods: 1) the combinatorial Hill and 2) the Monte Carlo simulation methods.

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