
A typed parallel λcalculus for graphbased communication
We introduce λ_∥  a simple yet powerful parallel extension of simply ty...
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Learning Attributed Graph Representations with Communicative Message Passing Transformer
Constructing appropriate representations of molecules lies at the core o...
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Probabilistic prototype models for attributed graphs
This contribution proposes a new approach towards developing a class of ...
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Graph Transformation Policy Network for Chemical Reaction Prediction
We address a fundamental problem in chemistry known as chemical reaction...
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Concept Drift and Anomaly Detection in Graph Streams
Graph representations offer powerful and intuitive ways to describe data...
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Chemical Transformation Motifs  Modelling Pathways as Integer Hyperflows
We present an elaborate framework for formally modelling pathways in che...
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Graph Transformation for Enzymatic Mechanisms
Motivation: The design of enzymes is as challenging as it is consequenti...
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A GraphBased Tool to Embed the πCalculus into a Computational DPO Framework
Graph transformation approaches have been successfully used to analyse and design chemical and biological systems. Here we build on top of a DPO framework, in which molecules are modelled as typed attributed graphs and chemical reactions are modelled as graph transformations. Edges and vertexes can be labelled with firstorder terms, which can be used to encode, e.g., steric information of molecules. While targeted to chemical settings, the computational framework is intended to be very generic and applicable to the exploration of arbitrary spaces derived via iterative application of rewrite rules, such as process calculi like Milner's πcalculus. To illustrate the generality of the framework, we introduce EpiM: a tool for computing execution spaces of πcalculus processes. EpiM encodes πcalculus processes as typed attributed graphs and then exploits the existing DPO framework to compute their dynamics in the form of graphs where nodes are πcalculus processes and edges are reduction steps. EpiM takes advantage of the graphbased representation and facilities offered by the framework, like efficient isomorphism checking to prune the space without resorting to explicit structural equivalences. EpiM is available as an online Pythonbased tool.
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