Jun Kikuchi

发表

Environmental metabolomics with data science for investigating ecosystem homeostasis.

Kengo Ito, Yasuhiro Date, Jun Kikuchi, 2018, Progress in nuclear magnetic resonance spectroscopy.

Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet

Yasuhiro Date, Jun Kikuchi, Yuka Shiokawa, 2018, Scientific Reports.

Exploratory machine-learned theoretical chemical shifts can closely predict metabolic mixture signals

Eisuke Chikayama, Kengo Ito, Yasuhiro Date, 2018, Chemical science.

NMR window of molecular complexity showing homeostasis in superorganisms.

Jun Kikuchi, Shunji Yamada, J. Kikuchi, 2017, The Analyst.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes

Jun Kikuchi, Tetsuo Noda, Maki Inoue, 2015, Scientific Reports.

Human metabolic, mineral, and microbiota fluctuations across daily nutritional intake visualized by a data-driven approach.

Yasuhiro Date, Jun Kikuchi, Y. Date, 2015, Journal of proteome research.

Metabolic dynamics analysis by massive data integration: application to tsunami-affected field soils in Japan.

Yasuhiro Date, Jun Kikuchi, Yuuri Tsuboi, 2015, ACS chemical biology.

Regional feature extraction of various fishes based on chemical and microbial variable selection using machine learning

Yasuhiro Date, Jun Kikuchi, Kenji Sakata, 2018 .

Development of KaPPA-View4 for omics studies on Jatropha and a database system KaPPA-Loader for construction of local omics databases

Yoshiyuki Ogata, Nozomu Sakurai, Masataka Kajikawa, 2012 .

Stable isotope labeling of Arabidopsis thaliana for an NMR-based metabolomics approach.

Kazuo Shinozaki, Jun Kikuchi, Takashi Hirayama, 2004, Plant & cell physiology.

Systematic NMR Analysis of Stable Isotope Labeled Metabolite Mixtures in Plant and Animal Systems: Coarse Grained Views of Metabolic Pathways

Kazuo Shinozaki, Eisuke Chikayama, Jun Kikuchi, 2008, PloS one.

Application of a Deep Neural Network to Metabolomics Studies and Its Performance in Determining Important Variables.

Yasuhiro Date, Jun Kikuchi, Y. Date, 2017, Analytical chemistry.

Statistical indices for simultaneous large-scale metabolite detections for a single NMR spectrum.

Kazuo Shinozaki, Kenji Akiyama, Eisuke Chikayama, 2010, Analytical chemistry.

Correlation exploration of metabolic and genomic diversity in rice

Kazuo Shinozaki, Jun Kikuchi, Kaworu Ebana, 2009, BMC Genomics.

Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses

Kazuki Saito, Satoshi Takamatsu, Jun Kikuchi, 2013, Metabolomics.

Transcriptome Analysis Uncovers a Growth-Promoting Activity of Orosomucoid-1 on Hepatocytes

Piero Carninci, Yoshihide Hayashizaki, Hideya Kawaji, 2017, EBioMedicine.

NMR-Based Metabolic Profiling of Field-Grown Leaves from Sugar Beet Plants Harbouring Different Levels of Resistance to Cercospora Leaf Spot Disease

Jun Kikuchi, Yasuyo Sekiyama, Seishi Ikeda, 2017, Metabolites.