18 citations · 27 across the 7 of their papers we have counts for
10 papers
Automated Deep Abstractions for Stochastic Chemical Reaction Networks
Tatjana Petrov, Denis Repin
Predicting stochastic cellular dynamics as emerging from the mechanistic models of molecular interactions is a long-standing challenge in systems biology: low-level chemical reacti…
Markov chain aggregation and its application to rule-based modelling
Tatjana Petrov
Rule-based modelling allows to represent molecular interactions in a compact and natural way. The underlying molecular dynamics, by the laws of stochastic chemical kinetics, behave…
Tropical Abstraction of Biochemical Reaction Networks with Guarantees
Andreea Beica, Jérôme Feret, Tatjana Petrov
Biochemical molecules interact through modification and binding reactions, giving raise to a combinatorial number of possible biochemical species. The time-dependent evolution of c…
Linear Distances between Markov Chains
Przemysław Daca, Thomas A. Henzinger, Jan Křetínský +1
We introduce a general class of distances (metrics) between Markov chains, which are based on linear behaviour. This class encompasses distances given topologically (such as the to…
Faster Statistical Model Checking for Unbounded Temporal Properties
Przemysław Daca, Thomas A. Henzinger, Jan Křetínský +1
We present a new algorithm for the statistical model checking of Markov chains with respect to unbounded temporal properties, such as reachability and full linear temporal logic. T…
Efficient reduction of Kappa models by static inspection of the rule-set
Andreea Beica, Calin Guet, Tatjana Petrov
When designing genetic circuits, the typical primitives used in major existing modelling formalisms are gene interaction graphs, where edges between genes denote either an activati…
Model Checking Gene Regulatory Networks
Mirco Giacobbe, Calin C. Guet, Ashutosh Gupta +3
The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace th…
Optimal Kullback-Leibler Aggregation via Information Bottleneck
Bernhard C. Geiger, Tatjana Petrov, Gernot Kubin +1
In this paper, we present a method for reducing a regular, discrete-time Markov chain (DTMC) to another DTMC with a given, typically much smaller number of states. The cost of redu…
Markov chain aggregation and its applications to combinatorial reaction networks
Arnab Ganguly, Tatjana Petrov, Heinz Koeppl
We consider a continuous-time Markov chain (CTMC) whose state space is partitioned into aggregates, and each aggregate is assigned a probability measure. A sufficient condition for…
Lumpability Abstractions of Rule-based Systems
Jerome Feret, Thomas Henzinger, Heinz Koeppl +1
The induction of a signaling pathway is characterized by transient complex formation and mutual posttranslational modification of proteins. To faithfully capture this combinatorial…