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Motoki Shiga

Showing results (1-10 of 18) with videos related to

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F1000Research|December 20, 2016
Two-step feature selection for predicting survival time of patients with metastatic castrate resistant prostate cancerMotoki Shiga
Microscopy (Oxford, England)|November 5, 2019
Application of machine learning techniques to electron microscopic/spectroscopic image data analysisShunsuke Muto, Motoki Shiga
IEEE/ACM Transactions on Computational Biology and Bioinformatics|September 11, 2015
Detecting Differentially Coexpressed Genes from Labeled Expression Data: A Brief ReviewMitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka
Bioinformatics (Oxford, England)|July 25, 2007
Annotating gene function by combining expression data with a modular gene networkMotoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Plos One|August 11, 2011
Genome-wide integration on transcription factors, histone acetylation and gene expression reveals genes co-regulated by histone modification patternsYayoi Natsume-Kitatani, Motoki Shiga, Hiroshi Mamitsuka
Genome Informatics. International Conference on Genome Informatics|March 19, 2010
Annotating gene functions with integrative spectral clustering on microarray expressions and sequencesLimin Li, Motoki Shiga, Wai-Ki Ching, et al.
Bioinformatics (Oxford, England)|September 9, 2009
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-dataMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Genome Informatics. International Conference on Genome Informatics|November 15, 2011
On the performance of methods for finding a switching mechanism in gene expressionMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Nucleic Acids Research|April 5, 2011
ROS-DET: robust detector of switching mechanisms in gene expressionMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Microscopy (Oxford, England)|May 17, 2024
Fast computational approach with prior dimension reduction for three-dimensional chemical component analysis using CT data of spectral imagingMotoki Shiga, Taisuke Ono, Kenichi Morishita, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
F1000Research|December 20, 2016
Two-step feature selection for predicting survival time of patients with metastatic castrate resistant prostate cancerMotoki Shiga
Microscopy (Oxford, England)|November 5, 2019
Application of machine learning techniques to electron microscopic/spectroscopic image data analysisShunsuke Muto, Motoki Shiga
IEEE/ACM Transactions on Computational Biology and Bioinformatics|September 11, 2015
Detecting Differentially Coexpressed Genes from Labeled Expression Data: A Brief ReviewMitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka
Bioinformatics (Oxford, England)|July 25, 2007
Annotating gene function by combining expression data with a modular gene networkMotoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Plos One|August 11, 2011
Genome-wide integration on transcription factors, histone acetylation and gene expression reveals genes co-regulated by histone modification patternsYayoi Natsume-Kitatani, Motoki Shiga, Hiroshi Mamitsuka
Genome Informatics. International Conference on Genome Informatics|March 19, 2010
Annotating gene functions with integrative spectral clustering on microarray expressions and sequencesLimin Li, Motoki Shiga, Wai-Ki Ching, et al.
Bioinformatics (Oxford, England)|September 9, 2009
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-dataMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Genome Informatics. International Conference on Genome Informatics|November 15, 2011
On the performance of methods for finding a switching mechanism in gene expressionMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Nucleic Acids Research|April 5, 2011
ROS-DET: robust detector of switching mechanisms in gene expressionMitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, et al.
Microscopy (Oxford, England)|May 17, 2024
Fast computational approach with prior dimension reduction for three-dimensional chemical component analysis using CT data of spectral imagingMotoki Shiga, Taisuke Ono, Kenichi Morishita, et al.
Pageof 2