S
Satoru Miyano
Researcher at Tokyo Medical and Dental University
Publications - 874
Citations - 45801
Satoru Miyano is an academic researcher from Tokyo Medical and Dental University. The author has contributed to research in topics: Gene & Gene regulatory network. The author has an hindex of 84, co-authored 811 publications receiving 38723 citations. Previous affiliations of Satoru Miyano include University of Paderborn & Institute of Medical Science.
Papers
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Journal ArticleDOI
Multi-omics approach for estimating metabolic networks using low-order partial correlations.
TL;DR: This work developed a statistical method based on low-order partial correlations with a robust correlation coefficient for estimating metabolic networks from metabolome, proteome, and transcriptome data and investigated the role of metabolites, enzymes, and enzyme genes that were identified as important factors in the network established by MF-PCor.
Journal ArticleDOI
D P 2 -complete lexicographically first maximal subgraph problems
TL;DR: The lexicographically first maximal (lfm) induced path problem is shown and the problem restricted dags with degree 3 is shown in NC2 while the problem for degree 4 is P-complete.
Learning Elementary Formal Systems and an Application to Discovering Motifs in Proteins
TL;DR: It is shown that H-EFS (m, k, t, r ) is polynomialtime learnable, which is the class of languages definable by EFSs consisting of at most m hereditary definite clauses with predicate symbols of arity at most r, where k and t bound the number of variable occurrences in the head and the number in the body, respectively.
Book ChapterDOI
Delta2p-Complete Lexicographically First Maximal Subgraph Problems
TL;DR: The lexicographically first maximal (lfm) induced path problem is shown and the problem restricted dags with degree 3 is shown in NC2 while the problem for degree 4 is P-complete.
Journal ArticleDOI
An efficient biological pathway layout algorithm combining grid-layout and spring embedder for complicated cellular location information
TL;DR: A new grid-layout algorithm based on the spring embedder algorithm that can handle location information and provide layouts with harmonized appearance is proposed and applied to three biological pathways; endothelial cell model, Fas-induced apoptosis model, and C. elegans cell fate simulation model.