T
Tomoyuki Higuchi
Researcher at University of Tokyo
Publications - 166
Citations - 5084
Tomoyuki Higuchi is an academic researcher from University of Tokyo. The author has contributed to research in topics: Data assimilation & Kalman filter. The author has an hindex of 30, co-authored 163 publications receiving 4673 citations. Previous affiliations of Tomoyuki Higuchi include University of California, Los Angeles & University of California, Berkeley.
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Approach to an irregular time series on the basis of the fractal theory
TL;DR: In this article, the fractal dimension of the set of points (t, f(t)) forming the graph of a function f defined on the unit interval was measured using a self-similarity property.
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Relationship between the fractal dimension and the power law index for a time series: a numerical investigation
TL;DR: In this paper, the relationship between the power law index α and the fractal dimension D for a time series following a power law spectrum is investigated by using a numerical experiment, and the relationships between α and D are also examined both for the differenced and for the integrated time series.
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Combining microarrays and biological knowledge for estimating gene networks via bayesian networks.
TL;DR: This work proposes a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-protein interactions, protein-DNA interactions, binding site information, existing literature and so on.
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Monte carlo filter using the genetic algorithm operators
TL;DR: This study tries to replace the step of the prediction by the mutation and crossover operators in the GA, and proposes a smoothing algorithm in which a massively simple parallel procedure plays an important role.
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Epidermal growth factor receptor tyrosine kinase defines critical prognostic genes of stage I lung adenocarcinoma.
Mai Yamauchi,Rui Yamaguchi,Asuka Nakata,Takashi Kohno,Masao Nagasaki,Teppei Shimamura,Seiya Imoto,Ayumu Saito,Kazuko Ueno,Yousuke Hatanaka,Ryo Yoshida,Tomoyuki Higuchi,Masaharu Nomura,David G. Beer,Jun Yokota,Satoru Miyano,Noriko Gotoh +16 more
TL;DR: It is re-emphasized that EGF signaling status in cancer cells underlies an aggressive phenotype of cancer cells, which is useful for the selection of early-stage lung adenocarcinoma patients with a poor prognosis.