Hiroshi Tsugawa
Hiroshi Tsugawa
Tokyo University of Agriculture and Technology
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MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis
H Tsugawa, T Cajka, T Kind, Y Ma, B Higgins, K Ikeda, M Kanazawa, ...
Nature methods 12 (6), 523-526, 2015
Hydrogen rearrangement rules: computational MS/MS fragmentation and structure elucidation using MS-FINDER software
H Tsugawa, T Kind, R Nakabayashi, D Yukihira, W Tanaka, T Cajka, ...
Analytical chemistry 88 (16), 7946-7958, 2016
Identification of small molecules using accurate mass MS/MS search
T Kind, H Tsugawa, T Cajka, Y Ma, Z Lai, SS Mehta, G Wohlgemuth, ...
Mass spectrometry reviews 37 (4), 513-532, 2018
Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics
Z Lai, H Tsugawa, G Wohlgemuth, S Mehta, M Mueller, Y Zheng, ...
Nature methods 15 (1), 53-56, 2018
Feature-based molecular networking in the GNPS analysis environment
LF Nothias, D Petras, R Schmid, K Dührkop, J Rainer, A Sarvepalli, ...
Nature methods 17 (9), 905-908, 2020
GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)
H Tsugawa, Y Tsujimoto, M Arita, T Bamba, E Fukusaki
BMC bioinformatics 12 (1), 1-13, 2011
Current metabolomics: technological advances
SP Putri, S Yamamoto, H Tsugawa, E Fukusaki
Journal of bioscience and bioengineering 116 (1), 9-16, 2013
Critical assessment of small molecule identification 2016: automated methods
EL Schymanski, C Ruttkies, M Krauss, C Brouard, T Kind, K Dührkop, ...
Journal of cheminformatics 9 (1), 1-21, 2017
Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis
H Tsugawa, T Bamba, M Shinohara, S Nishiumi, M Yoshida, E Fukusaki
Journal of bioscience and bioengineering 112 (3), 292-298, 2011
A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms
H Tsugawa, R Nakabayashi, T Mori, Y Yamada, M Takahashi, A Rai, ...
Nature methods 16 (4), 295-298, 2019
Bulk RNA degradation by nitrogen starvation‐induced autophagy in yeast
H Huang, T Kawamata, T Horie, H Tsugawa, Y Nakayama, Y Ohsumi, ...
The EMBO journal 34 (2), 154-168, 2015
A lipidome atlas in MS-DIAL 4
H Tsugawa, K Ikeda, M Takahashi, A Satoh, Y Mori, H Uchino, ...
Nature biotechnology 38 (10), 1159-1163, 2020
MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics
H Tsugawa, M Arita, M Kanazawa, A Ogiwara, T Bamba, E Fukusaki
Analytical chemistry 85 (10), 5191-5199, 2013
Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy
I Blaženović, T Kind, H Torbašinović, S Obrenović, SS Mehta, H Tsugawa, ...
Journal of cheminformatics 9 (1), 1-12, 2017
Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry
H Tsugawa, Y Tsujimoto, K Sugitate, N Sakui, S Nishiumi, T Bamba, ...
Journal of bioscience and bioengineering 117 (1), 122-128, 2014
Discovering regulated metabolite families in untargeted metabolomics studies
H Treutler, H Tsugawa, A Porzel, K Gorzolka, A Tissier, S Neumann, ...
Analytical chemistry 88 (16), 8082-8090, 2016
Advances in computational metabolomics and databases deepen the understanding of metabolisms
H Tsugawa
Current opinion in biotechnology 54, 10-17, 2018
Comprehensive identification of sphingolipid species by in silico retention time and tandem mass spectral library
H Tsugawa, K Ikeda, W Tanaka, Y Senoo, M Arita, M Arita
Journal of cheminformatics 9 (1), 1-12, 2017
MRMPROBS suite for metabolomics using large-scale MRM assays
H Tsugawa, M Kanazawa, A Ogiwara, M Arita
Bioinformatics 30 (16), 2379-2380, 2014
Retip: retention time prediction for compound annotation in untargeted metabolomics
P Bonini, T Kind, H Tsugawa, DK Barupal, O Fiehn
Analytical chemistry 92 (11), 7515-7522, 2020
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