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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Book ChapterDOI
Dynamic Bayesian Network and Nonparametric Regression for Nonlinear Modeling of Gene Networks from Time Series Gene Expression Data
TL;DR: A dynamic Bayesian network and nonparametric regression model for constructing a gene network from time series microarray gene expression data and derive a new criterion for evaluating an estimated network from Bayes approach is proposed.
Journal ArticleDOI
Modeling gene expression regulatory networks with the sparse vector autoregressive model
André Fujita,João Ricardo Sato,Humberto Miguel Garay-Malpartida,Rui Yamaguchi,Satoru Miyano,Mari Cleide Sogayar,Carlos Eduardo Ferreira +6 more
TL;DR: The proposed SVAR method is able to model gene regulatory networks in frequent situations in which the number of samples is lower than thenumber of genes, making it possible to naturally infer partial Granger causalities without any a priori information.
Journal ArticleDOI
BCOR and BCORL1 mutations in myelodysplastic syndromes and related disorders
Frederik Damm,Frederik Damm,Virginie Chesnais,Yasunobu Nagata,Kenichi Yoshida,Laurianne Scourzic,Laurianne Scourzic,Yusuke Okuno,Raphael Itzykson,Masashi Sanada,Yuichi Shiraishi,Véronique Gelsi-Boyer,Véronique Gelsi-Boyer,Aline Renneville,Satoru Miyano,Hiraku Mori,Lee-Yung Shih,Sophie Park,François Dreyfus,Agnès Guerci-Bresler,Eric Solary,Christian Rose,Stéphane Cheze,Thomas Prebet,Thomas Prebet,Norbert Vey,Norbert Vey,Marion Legentil,Yannis Duffourd,Stéphane de Botton,Claude Preudhomme,Daniel Birnbaum,Daniel Birnbaum,Olivier Bernard,Olivier Bernard,Seishi Ogawa,Michaela Fontenay,Olivier Kosmider +37 more
TL;DR: Deep sequencing data suggest that BCOR mutations define the clinical course rather than disease initiation, and despite infrequent mutations, BCOR analyses should be considered in risk stratification.
Journal ArticleDOI
Prediction of Transcriptional Terminators in Bacillus subtilis and Related Species
TL;DR: Terminal prediction can be used to reliably predict the operon structure in these organisms, even in the absence of experimentally known operons, as well as for the Firmicutes phylum in general.
Journal ArticleDOI
Profiling of somatic mutations in acute myeloid leukemia with FLT3-ITD at diagnosis and relapse
Manoj Garg,Yasunobu Nagata,Deepika Kanojia,Anand Mayakonda,Kenichi Yoshida,Sreya Haridas Keloth,Zhi Jiang Zang,Yusuke Okuno,Yuichi Shiraishi,Kenichi Chiba,Hiroko Tanaka,Satoru Miyano,Ling-Wen Ding,Tamara Alpermann,Qiao-Yang Sun,De-Chen Lin,Wenwen Chien,Vikas Madan,Li Zhen Liu,Kar Tong Tan,Abhishek Sampath,Subhashree Venkatesan,Koiti Inokuchi,Satoshi Wakita,Hiroki Yamaguchi,Wee Joo Chng,Shirley Kow Yin Kham,Allen Eng Juh Yeoh,Masashi Sanada,Joanna Schiller,Karl Anton Kreuzer,Steven M. Kornblau,Hagop M. Kantarjian,Torsten Haferlach,Michael Lill,Ming Chung Kuo,Lee Yung Shih,Igor Wolfgang Blau,Olga Blau,Henry Yang,Seishi Ogawa,H. Phillip Koeffler,H. Phillip Koeffler +42 more
TL;DR: This study clearly shows that FLT3-ITD AML requires additional driver genetic alterations in addition to FLT2-ITd alone, and DNMT3A mutations are the most stable mutations.