Takashi Kaburagi

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We investigated an in vitro metabolic test using rat liver biopsy samples by TLC-autoradioluminography (ARLG), with a view to developing a method to rapidly assess the drug metabolizing activities of individual patients. Drug metabolizing activity was measured in liver biopsy samples collected from rats in four groups: a female control group, male control(More)
We attempted to predict activity/dominance for soccer games, where activity is defined as the degree of activity of the game as perceived by the viewer, whereas dominance is the degree at which the viewer perceives a particular team to dominate over the other team. Such activity/dominance information would help a layman viewer understand the game. It would(More)
A novel algorithm is proposed for predicting transmembrane protein secondary structure from two-dimensional vector trajectories consisting of a hydropathy index and formal charge of a test amino acid sequence using stochastic dynamical system models. Two prediction problems are discussed. One is the prediction of transmembrane region counts; another is that(More)
This paper describes a novel vibration sensing system with wide dynamic range for measuring “scratching”, “turning over” and “sitting up/lying down” motions in an unconstrained manner while the patient is sleeping. The sensing device used in the proposed system is composed of a piezoceramic sensor sandwiched between two metal plates. Under the system’s(More)
Glucuronides of RT-3003 and its metabolite (9-OH-RT-3003), which was hydroxylated at the 9 position on the benzene ring, were separated by HPLC and identified by liquid chromatography (LC)/MS/MS and NMR. The conjugation sites of these glucuronides were determined by nuclear Overhauser effects (NOE) irradiation; RT-3003 was conjugated at an alcoholic(More)
We present an algorithm to predict gene regulatory network structure, where gene expression time series data are regarded as vector trajectories of the sample obtained from a stochastic dynamical system defined on a graph. We use a Gaussian Bayesian network for modeling a gene regulatory network structure. Here a node represents a gene, and a link between 2(More)
A new algorithm is proposed for predicting transmembrane regions from two dimensional vector trajectories consisting of hydropathy index and charge of a test amino acid sequence by stochastic dynamical system models. The prediction accuracy of a preliminary experiment is 96.09%. Since no fine-tuning is done, this appears encouraging.
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