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Testing conditional mean through regression model sequence using Yanai’s generalized coefficient of determination

Computational statistics & data analysis, 2021-06, Vol.158, p.107168, Article 107168

Ueki, Masao

2021

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Beta-negative binomial nonlinear spatio-temporal random effects modeling of COVID-19 case counts in Japan

Journal of applied statistics, 2023-05, Vol.50 (7), p.1650-1663

Ueki, Masao

2023

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Data-Adaptive Multivariate Test for Genomic Studies Using Fused Lasso

Mathematics (Basel), 2024-05, Vol.12 (10), p.1422

Ueki, Masao

2024

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On the choice of degrees of freedom for testing gene-gene interactions

Statistics in medicine, 2014-12, Vol.33 (28), p.4934-4948

Ueki, Masao

2014

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Artificial intelligence powered statistical genetics in biobanks

Journal of human genetics, 2021-01, Vol.66 (1), p.61-65

2021

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Automated acquisition of explainable knowledge from unannotated histopathology images

Nature communications, 2019-12, Vol.10 (1), p.5642-9, Article 5642

2019

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Artificial intelligence powered statistical genetics in biobanks

Journal of human genetics, 2021-01, Vol.66 (1), p.61-65

2021

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Smooth-threshold multivariate genetic prediction incorporating gene–environment interactions

G3 : genes - genomes - genetics, 2021-12, Vol.11 (12)

2021

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ENHANCING POWER OF SCORE TESTS FOR REGRESSION MODELS VIA FISHER TRANSFORMATION

Journal of the Japanese Society of Computational Statistics, 2018/04/20, Vol.30(2), pp.37-53

Ueki, Masao

2018

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Improved statistics for genome-wide interaction analysis

PLoS genetics, 2012-04, Vol.8 (4), p.e1002625-e1002625

2012

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Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

BMC bioinformatics, 2012-05, Vol.13 (1), p.72-72, Article 72

2012

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Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms

Scientific reports, 2020-12, Vol.10 (1), p.21726-21726, Article 21726

2020

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Bayesian generalized fused lasso modeling via NEG distribution

Communications in statistics. Theory and methods, 2019-08, Vol.48 (16), p.4132-4153

2019

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Clustering by phenotype and genome-wide association study in autism

Translational psychiatry, 2020-08, Vol.10 (1), p.290-290, Article 290

2020

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3.5KJPNv2: an allele frequency panel of 3552 Japanese individuals including the X chromosome

Human genome variation, 2019-06, Vol.6 (1), p.28-28, Article 28

2019

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Fast score test with global null estimation regardless of missing genotypes

PloS one, 2018-07, Vol.13 (7), p.e0199692-e0199692

2018

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Quick assessment for systematic test statistic inflation/deflation due to null model misspecifications in genome-wide environment interaction studies

PloS one, 2019-07, Vol.14 (7), p.e0219825

2019

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Outlier detection for questionnaire data in biobanks

International journal of epidemiology, 2019-08, Vol.48 (4), p.1305-1315

2019

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Detecting genetic association through shortest paths in a bidirected graph

Genetic epidemiology, 2017-09, Vol.41 (6), p.481-497

2017

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Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes

Translational psychiatry, 2020-08, Vol.10 (1), p.294-294, Article 294

2020

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A Mutation of COX6A1 Causes a Recessive Axonal or Mixed Form of Charcot-Marie-Tooth Disease

American journal of human genetics, 2014-09, Vol.95 (3), p.294-300

2014

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A pollen coat-inducible autoinhibited Ca2+-ATPase expressed in stigmatic papilla cells is required for compatible pollination in the Brassicaceae

The Plant cell, 2014-02, Vol.26 (2), p.636-649

2014

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Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection

Translational psychiatry, 2020-05, Vol.10 (1), p.157-157, Article 157

2020

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Interaction between Functional Connectivity and Neural Excitability in Autism: A Novel Framework for Computational Modeling and Application to Biological Data

Computational psychiatry, 2023, Vol.7 (1), p.14-29

2023

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Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods

Scientific reports, 2018-10, Vol.8 (1), p.14840-7, Article 14840

2018

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Testing conditional mean through regression model sequence using Yanai’s generalized coefficient of determination

Beta-negative binomial nonlinear spatio-temporal random effects modeling of COVID-19 case counts in Japan

Data-Adaptive Multivariate Test for Genomic Studies Using Fused Lasso

On the choice of degrees of freedom for testing gene-gene interactions

Artificial intelligence powered statistical genetics in biobanks

Automated acquisition of explainable knowledge from unannotated histopathology images

Artificial intelligence powered statistical genetics in biobanks

Smooth-threshold multivariate genetic prediction incorporating gene–environment interactions

ENHANCING POWER OF SCORE TESTS FOR REGRESSION MODELS VIA FISHER TRANSFORMATION

Improved statistics for genome-wide interaction analysis

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms

Bayesian generalized fused lasso modeling via NEG distribution

Clustering by phenotype and genome-wide association study in autism

3.5KJPNv2: an allele frequency panel of 3552 Japanese individuals including the X chromosome

Fast score test with global null estimation regardless of missing genotypes

Quick assessment for systematic test statistic inflation/deflation due to null model misspecifications in genome-wide environment interaction studies

Outlier detection for questionnaire data in biobanks

Detecting genetic association through shortest paths in a bidirected graph

Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes

A Mutation of COX6A1 Causes a Recessive Axonal or Mixed Form of Charcot-Marie-Tooth Disease

A pollen coat-inducible autoinhibited Ca2+-ATPase expressed in stigmatic papilla cells is required for compatible pollination in the Brassicaceae

Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection

Interaction between Functional Connectivity and Neural Excitability in Autism: A Novel Framework for Computational Modeling and Application to Biological Data

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods

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