human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "analysis of microarray data using artificial intelligence based techniques"):
  Abstract: Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli. As microarrays technologies have become more prevalent, the challenges of analyzing these data for getting better insight about biological processes have essentially increased. Due to availability of artificial intelligence based sophisticated computational techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, and many other nature-inspired algorithms, it is possible to analyse microarray gene expression data in more better way. Here, we reviewed artificial intelligence based techniques for the analysis of microarray gene expression data. Further, challenges in the field and future work direction have also been suggested.

Includes members:
  Member "formal concept analysis for knowledge discovery from biological data":
    also connected through other hyperedges:
      (none)
  Member "recurrent neural network based hybrid model for reconstructing gene regulatory network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fuzzy logic based approaches for gene regulatory network inference")
  Member "ant colony optimization for inferring key gene interactions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recurrent neural network based hybrid model for reconstructing gene regulatory network")
  Member "reconstruction and analysis of cancer specific gene regulatory networks from gene expression profiles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ant colony optimization for inferring key gene interactions")
  Member "a brief review of nature inspired algorithms for optimization":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comprehensive taxonomies of nature and bio inspired optimization inspiration versus algorithmic behavior critical analysis and recommendations")
  Member "a comprehensive evaluation of machine learning techniques for cancer class prediction based on microarray data":
    also connected through other hyperedges:
      (none)
  Member "evolutionary algorithms in genetic regulatory networks model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fuzzy logic based approaches for gene regulatory network inference")
  Member "a novel anticlustering filtering algorithm for the prediction of genes as a drug target":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a comprehensive evaluation of machine learning techniques for cancer class prediction based on microarray data")

Question: Please tell me which class the source paper 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.AI(Artificial Intelligence)