Takashi Ueda on Muck Rack

Takashi Ueda

Tokyo, Ōtemachi
As seen in: Nature, Wiley, Wiley Online Library, British Pharmacological Society, PLOS ONE, MDPI, Nikkei, Taylor & Francis Online, Science Magazine, The Cureus Journal of Medical Science and
Web3、スタートアップやベンチャー、社会起業家、ＳＤＧｓなどに関心があり、取材したり、大学で教えたりしています。イベントに参加するのも、主催するのも楽しみです。 facebook.com/uedatakashi2
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Articles

Comparative proteomic profiling of receptor kinase signaling reveals key trafficking components enforcing plant stomatal development

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By Wensai Shang, Ziyi Cai, Jiawei Tang, Pengfei Bai, Minh Vu, Minh Vũ, Chiaki Komatsu, Ophelia Papoulas, Kazuo Ebine, Akira Nozawa, Tatsuya Sawasaki, Takashi Ueda, Edward M. Marcotte, Keiko U. Torii
| Science Magazine Verified
Abstract Receptor kinases are pivotal for growth, development, and environmental response of plants. Yet, their regulatory mechanisms and spatial dynamics remain underexplored. The ERECTA-family receptor kinases coordinate diverse developmental processes, including stomatal development.
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DNA Methylation Levels at the C3orf37 Loci Correlate With Prostate Cancer Grade

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By Saya Ito, Takashi Ueda, Satoshi Sako, Yusuke Gabata
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. Supporting Information Filename Description iju70299-sup-0001-Supinfo.docxWord 2007 document , 124.2 KB Figure S1: Standard curves with primers for qMSP. Standard curves with primers for MSP analysis by qPCR were plotted based on the ratio of methylated and non-methylated DNA. The percentage displayed on the x-axis indicates the ratio of methylated DNA to the sum of methylated and non-methylated DNA.
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Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry

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By Masaya Sano, Yasuhiro Kanatani, Takashi Ueda, Shota Nemoto
| Taylor & Francis Online
Abstract Objective Ulcerative colitis (UC) is a chronic inflammatory bowel disease for which remission is dependent on corticosteroid (CS) treatment. The diversity of disease pathophysiology necessitates optimal case-specific treatment selection. This study aimed to identify prognostic factors for refractory UC using a machine learning model based on nationwide registry data.
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