His primary scientific interests are in Biochemistry, Metabolite, Metabolomics, Microbiology and Bacteria. His Metabolomics research is multidisciplinary, incorporating perspectives in Heteronuclear single quantum coherence spectroscopy, Extraction, Botany and Arabidopsis, Mutant. His studies in Microbiology integrate themes in fields like Probiotic, Epithelium, Intestinal epithelium, Bifidobacterium and Butyrate.
His Probiotic study integrates concerns from other disciplines, such as Lactobacillaceae and Genomic island. Jun Kikuchi combines subjects such as Omics, Linolenic acid and GC-content with his study of Bacteria. His Bifidobacterium longum research is multidisciplinary, incorporating elements of Actinomycetaceae and Shiga toxin, Enterobacteriaceae, Escherichia coli.
His scientific interests lie mostly in Biochemistry, Metabolomics, Metabolite, Biological system and Analytical chemistry. His Biochemistry research is multidisciplinary, relying on both Bacteria and Microbial population biology. He studies Probiotic, a branch of Bacteria.
His studies examine the connections between Metabolomics and genetics, as well as such issues in Ecosystem, with regards to Estuary and Artificial intelligence. Jun Kikuchi interconnects Chromatography and Computational biology in the investigation of issues within Metabolite. As part of the same scientific family, Jun Kikuchi usually focuses on Analytical chemistry, concentrating on Nuclear magnetic resonance spectroscopy and intersecting with Bioinformatics.
His primary scientific interests are in Biological system, Machine learning, Artificial intelligence, Metabolomics and Ecosystem. His studies deal with areas such as Macromolecule, Relaxation and Chemical shift as well as Biological system. His study in the field of Feature selection, Random forest and Feature is also linked to topics like Fish species and Matteuccia.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Tree and Computation. His research in Metabolomics intersects with topics in Artificial neural network, Coral and Cultivar, Horticulture. His Ecosystem study frequently draws connections between adjacent fields such as Probiotic.
His primary areas of study are Metabolomics, Artificial intelligence, Machine learning, Gut flora and Metabolome. His work deals with themes such as Particulate organic matter, Ecosystem, Natural ecosystem and Data science, which intersect with Metabolomics. His work on Ecosystem services is typically connected to Goby as part of general Ecosystem study, connecting several disciplines of science.
His research in the fields of Random forest, Artificial neural network, Data set and Ensemble learning overlaps with other disciplines such as Regression. The Gut flora study combines topics in areas such as Bacteroidaceae and Microbiology. Jun Kikuchi has researched Metabolome in several fields, including Microbiome and Ecology, Leopard, Coral.
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Commensal microbe-derived butyrate induces the differentiation of colonic regulatory T cells
Yukihiro Furusawa;Yuuki Obata;Shinji Fukuda;Takaho A. Endo.
Bifidobacteria can protect from enteropathogenic infection through production of acetate
Shinji Fukuda;Hidehiro Toh;Koji Hase;Kenshiro Oshima.
Comparative genome analysis of Lactobacillus reuteri and Lactobacillus fermentum reveal a genomic island for reuterin and cobalamin production.
Hidetoshi Morita;Hidehiro Toh;Shinji Fukuda;Hiroshi Horikawa.
DNA Research (2008)
Parkin binds the Rpn10 subunit of 26S proteasomes through its ubiquitin-like domain
Eri Sakata;Yoshiki Yamaguchi;Eiji Kurimoto;Jun Kikuchi.
EMBO Reports (2003)
PRIMe: a Web site that assembles tools for metabolomics and transcriptomics.
Kenji Akiyama;Eisuke Chikayama;Hiroaki Yuasa;Yukihisa Shimada.
in Silico Biology (2008)
Dual biosynthetic pathways to phytosterol via cycloartenol and lanosterol in Arabidopsis.
Kiyoshi Ohyama;Masashi Suzuki;Jun Kikuchi;Kazuki Saito.
Proceedings of the National Academy of Sciences of the United States of America (2009)
Spectroscopic and Mutational Analysis of the Blue-Light Photoreceptor AppA: A Novel Photocycle Involving Flavin Stacking with an Aromatic Amino Acid†
Brian J Kraft;Shinji Masuda;Jun Kikuchi;Vladimira Dragnea.
Dissection of genotype–phenotype associations in rice grains using metabolome quantitative trait loci analysis
Fumio Matsuda;Yozo Okazaki;Akira Oikawa;Miyako Kusano.
Plant Journal (2012)
Statistical indices for simultaneous large-scale metabolite detections for a single NMR spectrum.
Eisuke Chikayama;Yasuyo Sekiyama;Mami Okamoto;Yumiko Nakanishi.
Analytical Chemistry (2010)
Strengthening of the intestinal epithelial tight junction by Bifidobacterium bifidum
Chen Yu Hsieh;Toshifumi Osaka;Eri Moriyama;Yasuhiro Date.
Physiological Reports (2015)
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