human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "bigraphical models for protein and membrane interactions"
  Abstract: We present a bigraphical framework suited for modeling biological systems both at protein level and at membrane level. We characterize formally bigraphs corresponding to biologically meaningful systems, and bigraphic rewriting rules representing biologically admissible interactions. At the protein level, these bigraphic reactive systems correspond exactly to systems of k-calculus. Membrane-level interactions are represented by just two general rules, whose application can be triggered by proteinlevel interactions in a well-defined and precise way. This framework can be used to compare and merge models at different abstraction levels; in particular, higher-level (e.g. mobility) activities can be given a formal biological justification in terms of low-level (i.e., protein) interactions. As examples, we formalize in our framework the vesiculation and the phagocytosis processes. Cardelli in [8] has convincingly argued that the various biochemical toolkits identified by biologists can be described as a hierarchy of abstract machines, each of which can be modelled using methods and techniques from concurrency theory. These machines are highly interdependent: “to understand the functioning of a cell, one must understand also how the various machines interact” [8]. Like other complex situations, it seems unlikely to find a single notation covering all aspects of a whole organism. In fact, we are in presence of a tower of models [19], each focusing on specific aspects of the biological system, at different levels of abstractions. Higher-level models must be represented, orrealised, at a lower level, and where possible this representation must be proved sound; in addition, we need to combine different models at the same level. To this end, we need a general metamodel, that is, a framework, where these models (possibly at different abstraction levels) can be encoded, and their interactions can be formally described. In this paper, we substantiate Milner’s idea that bigraphs can be successfully used as a framework for systems biology. More precisely, we define a class of biological bigraphs, and biological bigraphical reactive systems (BioRS), for dealing with both protein-level and membrane-level interactions. An important design choice is that this framework has to be biologically sound, i.e., it must admit only systems and reactions which are biologically meaningful, especially at lower level machines (i.e. protein). In this way, encoding a given model, for any abstract machine, as a BioRS provides automatically a formal, biologically sound justification for the model (or “implementation”) in terms of protein reactions and explains how its membrane-level interactions are realised by protein machinery. In order to formalize this “biological soundness”, we need a formal protein model to compare to our framework. We choose Danos and Laneve’s k-calculus, one of the most accepted formal model of protein systems. By suitable sorting conditions, we define a bigraphical framework which allows all and only protein configurations and interactions of the k-calculus. It is important to notice, however, that our methodology is general, and can be applied to other formal protein models. On the other hand, membrane nesting reconfiguration can be performed by just only two general rules, corresponding to the natural phenomena of “pinch” and “fuse” [10]. For encoding a given membrane model one has just to refine this general schema by specifying when these reactions are triggered,

Connected through hyperedge HE-1 (induced by source paper "towards a formal model for composable container systems"):
  with members:
    - "distributed execution of bigraphical reactive systems"
    - "a csp implementation of the bigraph embedding problem"

Connected through hyperedge HE-2 (induced by source paper "distributed execution of bigraphical reactive systems"):
  with members:
    - "a csp implementation of the bigraph embedding problem"

Connected through hyperedge HE-3 (induced by source paper "a csp implementation of the bigraph embedding problem"):
  with members:
    - "distributed execution of bigraphical reactive systems"

Connected through hyperedge HE-4 (induced by source paper "implementing the stochastics brane calculus in a generic stochastic abstract machine"):
  with members:
    - "measurable stochastics for brane calculus"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CE(Computational Engineering, Finance, and Science)