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Yojiro Sakiyama

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Expert Opinion on Drug Metabolism & Toxicology|February 26, 2009
The use of machine learning and nonlinear statistical tools for ADME predictionYojiro Sakiyama
Nuclear Medicine and Biology|May 25, 2006
Acute treatment with pentobarbital alters the kinetics of in vivo receptor binding in the mouse brainYojiro Sakiyama, Masao Saito, Osamu Inoue
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|October 16, 2008
[Application of nonlinear regression model to sigmoid dose-response relationship in pharmacological studies]Yojiro Sakiyama, Katsuyo Ohashi, Yukio Takahashi
Yakugaku Zasshi : Journal of the Pharmaceutical Society of Japan|December 7, 2007
[Analysis of censored data in multi-factorial analgesic test]Yojiro Sakiyama, Osamu Komiyama, Hideo Tsukada
Journal of Neuroscience Methods|September 21, 2007
A novel automated method for measuring the effect of analgesics on formalin-evoked licking behavior in ratsYojiro Sakiyama, Tetsujo Sujaku, Akihiro Furuta
Digestive Diseases and Sciences|December 21, 2007
Pathophysiological characteristics of dimethylnitrosamine-induced liver fibrosis in acute and chronic injury models: a possible contribution of KLF5 to fibrogenic responsesFumihiro Ohara, Aisuke Nii, Yojiro Sakiyama, et al.
Innovations in Clinical Neuroscience|May 1, 2013
Predicting pharmacokinetic stability by multiple oral administration of atypical antipsychoticsAkihide Wakamatsu, Kazuo Aoki, Yojiro Sakiyama, et al.
Annals of Nuclear Medicine|October 24, 2007
Stimulation of adenosine A1 receptors decreases in vivo dopamine D1 receptor binding of [11C]SCH23390 in the cat striatum revealed by positron emission tomographyYojiro Sakiyama, Kentaro Hatano, Takashi Kato, et al.
Annals of Nuclear Medicine|October 24, 2007
An atlas-based image registration method for dopamine receptor imaging with PET in ratsYojiro Sakiyama, Kentaro Hatano, Toshihisa Tajima, et al.
Journal of Molecular Graphics & Modelling|August 9, 2007
Predicting human liver microsomal stability with machine learning techniquesYojiro Sakiyama, Hitomi Yuki, Takashi Moriya, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
Expert Opinion on Drug Metabolism & Toxicology|February 26, 2009
The use of machine learning and nonlinear statistical tools for ADME predictionYojiro Sakiyama
Nuclear Medicine and Biology|May 25, 2006
Acute treatment with pentobarbital alters the kinetics of in vivo receptor binding in the mouse brainYojiro Sakiyama, Masao Saito, Osamu Inoue
Nihon Yakurigaku Zasshi. Folia Pharmacologica Japonica|October 16, 2008
[Application of nonlinear regression model to sigmoid dose-response relationship in pharmacological studies]Yojiro Sakiyama, Katsuyo Ohashi, Yukio Takahashi
Yakugaku Zasshi : Journal of the Pharmaceutical Society of Japan|December 7, 2007
[Analysis of censored data in multi-factorial analgesic test]Yojiro Sakiyama, Osamu Komiyama, Hideo Tsukada
Journal of Neuroscience Methods|September 21, 2007
A novel automated method for measuring the effect of analgesics on formalin-evoked licking behavior in ratsYojiro Sakiyama, Tetsujo Sujaku, Akihiro Furuta
Digestive Diseases and Sciences|December 21, 2007
Pathophysiological characteristics of dimethylnitrosamine-induced liver fibrosis in acute and chronic injury models: a possible contribution of KLF5 to fibrogenic responsesFumihiro Ohara, Aisuke Nii, Yojiro Sakiyama, et al.
Innovations in Clinical Neuroscience|May 1, 2013
Predicting pharmacokinetic stability by multiple oral administration of atypical antipsychoticsAkihide Wakamatsu, Kazuo Aoki, Yojiro Sakiyama, et al.
Annals of Nuclear Medicine|October 24, 2007
Stimulation of adenosine A1 receptors decreases in vivo dopamine D1 receptor binding of [11C]SCH23390 in the cat striatum revealed by positron emission tomographyYojiro Sakiyama, Kentaro Hatano, Takashi Kato, et al.
Annals of Nuclear Medicine|October 24, 2007
An atlas-based image registration method for dopamine receptor imaging with PET in ratsYojiro Sakiyama, Kentaro Hatano, Toshihisa Tajima, et al.
Journal of Molecular Graphics & Modelling|August 9, 2007
Predicting human liver microsomal stability with machine learning techniquesYojiro Sakiyama, Hitomi Yuki, Takashi Moriya, et al.
Pageof 2