| Variable selection for functional regression models via the L1 regularization H Matsui, S Konishi Computational Statistics & Data Analysis 55 (12), 3304-3310, 2011 | 116 | 2011 |
| Metabolic adaptation to nutritional stress in human colorectal cancer M Miyo, M Konno, N Nishida, T Sueda, K Noguchi, H Matsui, H Colvin, ... Scientific reports 6 (1), 38415, 2016 | 66 | 2016 |
| Functional logistic discrimination via regularized basis expansions Y Araki, S Konishi, S Kawano, H Matsui Communications in Statistics-Theory and Methods 38 (16-17), 2944-2957, 2009 | 54 | 2009 |
| スパース推定法による統計モデリング 川野秀一松井秀俊廣瀬慧 | 44* | 2018 |
| MicroRNAs induce epigenetic reprogramming and suppress malignant phenotypes of human colon cancer cells H Ogawa, X Wu, K Kawamoto, N Nishida, M Konno, J Koseki, H Matsui, ... PLoS One 10 (5), e0127119, 2015 | 44 | 2015 |
| Variable and boundary selection for functional data via multiclass logistic regression modeling H Matsui Computational Statistics & Data Analysis 78, 176-185, 2014 | 40 | 2014 |
| Nonlinear regression modeling via the lasso-type regularization S Tateishi, H Matsui, S Konishi Journal of statistical planning and inference 140 (5), 1125-1134, 2010 | 35 | 2010 |
| Functional regression modeling via regularized Gaussian basis expansions Y Araki, S Konishi, S Kawano, H Matsui Annals of the Institute of Statistical Mathematics 61, 811-833, 2009 | 35 | 2009 |
| Regularized functional regression modeling for functional response and predictors H Matsui, S Konishi Journal of Math-for-Industry 1, 17-25, 2009 | 33 | 2009 |
| Multivariate regression modeling for functional data H Matsui, Y Araki, S Konishi Journal of Data Science 6 (3), 313-331, 2008 | 32 | 2008 |
| Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon S Koda, Y Onda, H Matsui, K Takahagi, Y Uehara-Yamaguchi, M Shimizu, ... Frontiers in plant science 8, 2055, 2017 | 21 | 2017 |
| Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection M Kayano, H Matsui, R Yamaguchi, S Imoto, S Miyano Biostatistics 17 (2), 235-248, 2016 | 21 | 2016 |
| Embryonic microRNA-369 controls metabolic splicing factors and urges cellular reprograming M Konno, J Koseki, K Kawamoto, N Nishida, H Matsui, DL Dewi, M Ozaki, ... PLoS One 10 (7), e0132789, 2015 | 21 | 2015 |
| Mathematical analysis predicts imbalanced IDH1/2 expression associates with 2-HG-inactivating β-oxygenation pathway in colorectal cancer J Koseki, H Colvin, T Fukusumi, N Nishida, M Konno, K Kawamoto, ... International journal of oncology 46 (3), 1181-1191, 2015 | 19 | 2015 |
| Pyruvate kinase M2, but not M1, allele maintains immature metabolic states of murine embryonic stem cells M Konno, H Ishii, J Koseki, N Tanuma, N Nishida, K Kawamoto, ... Regenerative Therapy 1, 63-71, 2015 | 18* | 2015 |
| Quadratic regression for functional response models H Matsui Econometrics and Statistics 13, 125-136, 2020 | 16 | 2020 |
| A trans-omics mathematical analysis reveals novel functions of the ornithine metabolic pathway in cancer stem cells J Koseki, H Matsui, M Konno, N Nishida, K Kawamoto, Y Kano, M Mori, ... Scientific reports 6 (1), 20726, 2016 | 16 | 2016 |
| Sparse group lasso for multiclass functional logistic regression models H Matsui Communications in Statistics-Simulation and Computation 48 (6), 1784-1797, 2019 | 13 | 2019 |
| Causal discovery for linear mixed data Y Zeng, S Shimizu, H Matsui, F Sun Conference on Causal Learning and Reasoning, 994-1009, 2022 | 10 | 2022 |
| Multiclass functional discriminant analysis and its application to gesture recognition H Matsui, T Araki, S Konishi Journal of classification 28, 227-243, 2011 | 10 | 2011 |
Yuko ArakiProfessor, Tohoku UniversityVerified email at tohoku.ac.jp
