Abstract: The present invention provides a marker which can be used as an indicator for efficacy prediction of an mTOR related anticancer agent or prognostic prediction, and a novel anticancer agent. The present invention provides a method for efficacy evaluation of a cancer drug, and, specifically, a prediction method for the efficacy of an mTOR-related cancer drug by detecting NRF2 abnormality. In addition, the present invention provides a prognostic prediction method for cancer, and, specifically, a prediction method for the prognosis of cancer by detecting NRF2 abnormality. Furthermore, the present invention provides a novel anticancer agent that targets NRF2.

Abstract: The present invention provides a marker which can be used as an indicator for efficacy prediction of an mTOR related anticancer agent or prognostic prediction, and a novel anticancer agent. The present invention provides a method for efficacy evaluation of a cancer drug, and, specifically, a prediction method for the efficacy of an mTOR-related cancer drug by detecting NRF2 abnormality. In addition, the present invention provides a prognostic prediction method for cancer, and, specifically, a prediction method for the prognosis of cancer by detecting NRF2 abnormality. Furthermore, the present invention provides a novel anticancer agent that targets NRF2.

Abstract: An emergency call panel which comprises call buttons previously assigned to standard calls transmitted from an emergency call server of an emergency communication system, and transmission buttons for transmitting the data regarding the call selected from the standard calls to a call server in situation that one of the call buttons is selected in response to one of the standard calls. An emergency call system comprising a call server and an emergency call panel for carrying out the call processing of the call server, which comprises selecting the call button in response to the standard call based on call content and sending an initiation demand data including the selected data for standard call to the call server at the emergency call panel, and carrying out the call processing at the call server when the call server receives the initiation demand data.

Abstract: A graphical Gaussian modeling method capable of speedily and accurately estimating a genetic network from an expression profile and an apparatus therefore are provided. The present invention provides a graphical Gaussian modeling method for estimating a genetic network including the steps of (a) clustering genes based on an expression profile, (b) selecting genes having a profile closest to a mean value of an expression profile per cluster to be used as representative genes representing the cluster, (c) obtaining a correlation coefficient matrix among representative genes, (d) obtaining a partial correlation coefficient matrix from the correlation coefficient matrix, (e) contracting the partial correlation coefficient matrix according to predetermined conditions and (f) displaying a contracted model based on the contracted partial correlation coefficient matrix.

Abstract: The invention has the object of obtaining, at a high rate of success, graphs indicating the relationships between variables indicating the states of observed items which are the subjects of data mining, and improving the reliability of the outputted graphs. A method for generating a graph showing the relationships between variables comprises a step S2 of establishing a number of graphs to be generated, a step S5 of randomly establishing an order of variables X forming the set of all variables V, a step S6 of performing a process of reconstructing a graph showing the relationships between variables, and a step S10 of outputting a comprehensive graph including all edges existing in any of the graphs generated with each graph generation.

Abstract: A graphical Gaussian modeling method capable of speedily and accurately estimating a genetic network from an expression profile and an apparatus therefore are provided. The present invention provides a graphical Gaussian modeling method for estimating a genetic network including the steps of (a) clustering genes based on an expression profile, (b) selecting genes having a profile closest to a mean value of an expression profile per cluster to be used as representative genes representing the cluster, (c) obtaining a correlation coefficient matrix among representative genes, (d) obtaining a partial correlation coefficient matrix from the correlation coefficient matrix, (e) contracting the partial correlation coefficient matrix according to predetermined conditions and (f) displaying a contracted model based on the contracted partial correlation coefficient matrix.