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 "single particle cryo electron microscopy mathematical theory computational challenges and opportunities"):
  Abstract: In recent years, an abundance of new molecular structures have been elucidated using cryo-electron microscopy (cryo-EM), largely due to advances in hardware technology and data processing techniques. Owing to these new exciting developments, cryo-EM was selected by Nature Methods as Method of the Year 2015, and the Nobel Prize in Chemistry 2017 was awarded to three pioneers in the field. #R##N#The main goal of this article is to introduce the challenging and exciting computational tasks involved in reconstructing 3-D molecular structures by cryo-EM. Determining molecular structures requires a wide range of computational tools in a variety of fields, including signal processing, estimation and detection theory, high-dimensional statistics, convex and non-convex optimization, spectral algorithms, dimensionality reduction, and machine learning. The tools from these fields must be adapted to work under exceptional conditions, including extreme noise levels, the presence of missing data, and massively large datasets in the order of several Terabytes. #R##N#In addition, we present two statistical models: multi-reference alignment and multi-target detection, that abstract away much of the intricacies of cryo-EM, while retaining some of its essential features. Based on these abstractions, we discuss some recent intriguing results in the mathematical theory of cryo-EM, and delineate relations with group theory, invariant theory, and information theory. We conclude the article by listing the computational and theoretical challenges that still lie ahead.

Includes members:
  Member "unsupervised particle sorting for high resolution single particle cryo em":
    also connected through other hyperedges:
      (none)
  Member "a common lines approach for ab initio modeling of cyclically symmetric molecules":
    also connected through other hyperedges:
      (none)
  Member "multi target detection with application to cryo electron microscopy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi target detection with an arbitrary spacing distribution")
  Member "apple picker automatic particle picking a low effort cryo em framework":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "image based size analysis of agglomerated and partially sintered particles via convolutional neural networks")
  Member "toward single particle reconstruction without particle picking breaking the detection limit":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi target detection with application to cryo electron microscopy")
  Member "estimation in the group action channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spectral methods from tensor networks")
  Member "bispectrum inversion with application to multireference alignment":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi target detection with application to cryo electron microscopy")
  Member "heterogeneous multireference alignment a single pass approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "harmonic alignment")

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.IT(Information Theory)