human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "Missing value imputation for gene expression data: computational techniques to recover missing data from available information"
  Abstract: Microarray gene expression data generally suffers from missing value problem due to a variety of experimental reasons. Since the missing data points can adversely affect downstream analysis, many algorithms have been proposed to impute missing values. In this survey, we provide a comprehensive review of existing missing value imputation algorithms, focusing on their underlying algorithmic techniques and how they utilize local or global information from within the data, or their use of domain knowledge during imputation. In addition, we describe how the imputation results can be validated and the different ways to assess the performance of different imputation algorithms, as well as a discussion on some possible future research directions. It is hoped that this review will give the readers a good understanding of the current development in this field and inspire them to come up with the next generation of imputation algorithms.

Connected through hyperedge HE-1 (induced by source paper "Noisy values detection and correction of traffic accident data"):
  with members:
    (none)

Connected through hyperedge HE-2 (induced by source paper "A Bayesian missing value estimation method for gene expression profile data."):
  with members:
    - "Missing value estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme"
    - "Online Model Selection Based on the Variational Bayes"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science