Research theme for competitive and other funds (1)：
2013 - 2016 Analysis of relationship between genetic variation and growth/phenotypic characters of wild Oryza accessions using GWAS
Papers (40)：
Taichi Nukui, Akio Onogi. An R package for ensemble learning stacking. Bioinformatics Advances. 2023. 3. 1
Daiki Oda, Akio Onogi. Assessing the predictability of racing performance of Thoroughbreds using mixed-effects model. Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie. 2023
Akio Onogi. A Bayesian model for genomic prediction using metabolic networks. Bioinformatics Advances. 2023. 3. 1
Daiki TERAMOTO, Akio ONOGI. Optimization of Soybean Phenological Models Using Historical Data of Breeding and Comparison of Optimization Methods. Japanese Journal of Crop Science. 2023. 92. 1. 28-40
Akio Onogi, Aisaku Arakawa. An R package VIGoR for joint estimation of multiple linear learners with variational Bayesian inference. Bioinformatics (Oxford, England). 2022
小野木 章雄. ヒストリカルデータの作物育種への利用に向けて-Towards utilization of historical data for crop breeding-特集 スマート育種の展開 : 現状と将来展望. JATAFFジャーナル = JATAFF journal : 農林水産技術. 2022. 10. 12. 17-23
Akio Onogi. Integration of Crop Growth Models and Genomic Prediction. Methods in molecular biology (Clifton, N.J.). 2022. 2467. 359-396
小野木章雄, 藤井健一朗, 菊池彰夫, 小松邦彦, 河野雄飛, 大木信彦, 渡邊啓史, 加賀秋人. Prediction of flowering and maturity time of soybean using genes and meteorological factors. 育種学研究. 2022. 24
小野木章雄. A Bayesian model for genomic prediction utilizing metabolite networks. 育種学研究. 2021. 23
法隆大輔, 小野木章雄, 林武司. Visualization of the crop trait ontology using Cytoscape.js library. 育種学研究. 2021. 23
