Hee-Jin Yoon

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Since microarray data have gene data consisting of large amounts of data, to improve the performance of cancer classification, features of useful data should be extracted. The present paper presents a method of classifying lymphoma cancers by extracting 20 data each from 4026 lymphoma data out of microarray data through a t-test and Euclidean distances(More)
As a reverse engineering field, reconstructing a Gene Regulatory Network (GRN) from time series gene data has been a challenging issue in bioinformatics. This paper proposes a novel engineering framework that infers and reconstructs a gene regulatory network in terms of regulatory accuracy. Different from other statistical methods, the proposed framework(More)
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