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: "ant colony optimization for inferring key gene interactions"
  Abstract: Inferring gene interaction network from gene expression data is an important task in systems biology research. The gene interaction network, especially key interactions, plays an important role in identifying biomarkers for disease that further helps in drug design. Ant colony optimization is an optimization algorithm based on natural evolution and has been used in many optimization problems. In this paper, we applied ant colony optimization algorithm for inferring the key gene interactions from gene expression data. The algorithm has been tested on two different kinds of benchmark datasets and observed that it successfully identify some key gene interactions.

Connected through hyperedge HE-1 (induced by source paper "recurrent neural network based hybrid model for reconstructing gene regulatory network"):
  with members:
    - "evolutionary algorithms in genetic regulatory networks model"

Connected through hyperedge HE-2 (induced by source paper "analysis of microarray data using artificial intelligence based techniques"):
  with members:
    - "formal concept analysis for knowledge discovery from biological data"
    - "recurrent neural network based hybrid model for reconstructing gene regulatory network"
    - "reconstruction and analysis of cancer specific gene regulatory networks from gene expression profiles"
    - "a brief review of nature inspired algorithms for optimization"
    - "a comprehensive evaluation of machine learning techniques for cancer class prediction based on microarray data"
    - "evolutionary algorithms in genetic regulatory networks model"
    - "a novel anticlustering filtering algorithm for the prediction of genes as a drug target"
    - "artificial neural networks for beginners"

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.NE(Neural and Evolutionary Computing)