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 estimation for DNA microarray gene expression data by Support Vector Regression imputation and orthogonal coding scheme"
  Abstract: Background
Gene expression profiling has become a useful biological resource in recent years, and it plays an important role in a broad range of areas in biology. The raw gene expression data, usually in the form of large matrix, may contain missing values. The downstream analysis methods that postulate complete matrix input are thus not applicable. Several methods have been developed to solve this problem, such as K nearest neighbor impute method, Bayesian principal components analysis impute method, etc. In this paper, we introduce a novel imputing approach based on the Support Vector Regression (SVR) method. The proposed approach utilizes an orthogonal coding input scheme, which makes use of multi-missing values in one row of a certain gene expression profile and imputes the missing value into a much higher dimensional space, to obtain better performance.

Connected through hyperedge HE-1 (induced by source paper "A Bayesian missing value estimation method for gene expression profile data."):
  with members:
    - "Online Model Selection Based on the Variational Bayes"
    - "Missing value imputation for gene expression data: computational techniques to recover missing data from available information"

Connected through hyperedge HE-2 (induced by source paper "Experiment specific expression patterns."):
  with members:
    (none)

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