Yasuhiro Date
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Explore the profile of Yasuhiro Date including associated specialties, affiliations and a list of published articles.
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48
Citations
760
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Recent Articles
1.
Ishikawa C, Date Y, Umeda M, Tarumoto Y, Okubo M, Morimitsu Y, et al.
Metabolites
. 2024 Apr;
14(4).
PMID: 38668371
Sugarcane ( spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better...
2.
Date Y, Ishikawa C, Umeda M, Tarumoto Y, Okubo M, Tamura Y, et al.
Metabolites
. 2022 Sep;
12(9).
PMID: 36144266
Sugarcane is essential for global sugar production and its compressed juice is a key raw material for industrial products. Sugarcane juice includes various metabolites with abundances and compositional balances influencing...
3.
Date Y, Wei F, Tsuboi Y, Ito K, Sakata K, Kikuchi J
BMC Chem
. 2021 Feb;
15(1):13.
PMID: 33610164
Nuclear magnetic resonance (NMR)-based relaxometry is widely used in various fields of research because of its advantages such as simple sample preparation, easy handling, and relatively low cost compared with...
4.
Wei F, Ito K, Sakata K, Asakura T, Date Y, Kikuchi J
Sci Rep
. 2021 Feb;
11(1):3766.
PMID: 33580151
Functional diversity rather than species richness is critical for the understanding of ecological patterns and processes. This study aimed to develop novel integrated analytical strategies for the functional characterization of...
5.
Ichihashi Y, Date Y, Shino A, Shimizu T, Shibata A, Kumaishi K, et al.
Proc Natl Acad Sci U S A
. 2020 Jun;
117(25):14552-14560.
PMID: 32513689
Both inorganic fertilizer inputs and crop yields have increased globally, with the concurrent increase in the pollution of water bodies due to nitrogen leaching from soils. Designing agroecosystems that are...
6.
Wei F, Fukuchi M, Ito K, Sakata K, Asakura T, Date Y, et al.
Molecules
. 2020 Apr;
25(8).
PMID: 32340308
Conventional proton nuclear magnetic resonance (H-NMR) has been widely used for identification and quantification of small molecular components in food. However, identification of major soluble macromolecular components from conventional H-NMR...
7.
Ito K, Obuchi Y, Chikayama E, Date Y, Kikuchi J
Chem Sci
. 2018 Dec;
9(43):8213-8220.
PMID: 30542569
Various chemical shift predictive methodologies have been studied and developed, but there remains the problem of prediction accuracy. Assigning the NMR signals of metabolic mixtures requires high predictive performance owing...
8.
Kato T, Yamazaki K, Nakajima M, Date Y, Kikuchi J, Hase K, et al.
mSphere
. 2018 Oct;
3(5).
PMID: 30333180
Periodontal disease induced by periodontopathic bacteria like is demonstrated to increase the risk of metabolic, inflammatory, and autoimmune disorders. Although precise mechanisms for this connection have not been elucidated, we...
9.
Asakura T, Date Y, Kikuchi J
Anal Chim Acta
. 2018 Oct;
1037:230-236.
PMID: 30292297
Deep neural network (DNN) is a useful machine learning approach, although its applicability to metabolomics studies has rarely been explored. Here we describe the development of an ensemble DNN (EDNN)...
10.
Profiling physicochemical and planktonic features from discretely/continuously sampled surface water
Oita A, Tsuboi Y, Date Y, Oshima T, Sakata K, Yokoyama A, et al.
Sci Total Environ
. 2018 Apr;
636:12-19.
PMID: 29702398
There is an increasing need for assessing aquatic ecosystems that are globally endangered. Since aquatic ecosystems are complex, integrated consideration of multiple factors utilizing omics technologies can help us better...