Abstract:
The present invention relates to a method for estimating a novel drug regeneration candidate based on EMR and drug/disease network information by using a novel drug regeneration candidate estimation system including a computer-readable recording medium. The method according to an embodiment of the present invention includes the steps of: a) configuring a binary drug/disease network based on the information regarding a target disease of a specific drug; b) extracting relevant information based on EMR or clinical physiomics and genomic signatures; c) configuring a drug-drug/disease-disease similarity matrix according to the EMR or clinical physiomics; d) computing a drug-disease edge score (P_ c) based on the EMR or clinical physiomics according to the similarity matrix; e) extracting the information genomically relevant to the drugs and the diseases based on the EMR or clinical physiomics and genomic signatures; f) configuring the drug-drug/disease-disease similarity matrix according to the the genomic signatures; g) calculating another drug-disease edge score (P_g) based on the genomic signatures according to the similarity matrix; h) calculating the final estimation score of the edge f(e_ij) by using the P_c and P_g; and i) determining whether the label value of the f(e_ij) is true or false based on a cut-off value.
Abstract:
본 발명은 개별 단백질 또는 유전자의 정적 특성, 이웃 단백질과의 단백질 상호작용 정보, 단백질 또는 유전자의 발현 프로파일 등을 입력함으로써 소정의 시간 및 외부자극 조건에서 대상 단백질의 세포 내 위치 정보를 포함한 동적인 기능 정보를 예측할 수 있는 방법을 제공한다. 본 발명에 의한 방법을 이용함으로써 기존에 공지된 대상 단백질과 소정의 시간 및 외부자극 조건을 입력함으로써 특정 시간 및 외부자극 조건에서 대상 단백질의 세포 내 위치 정보를 포함한 동적인 기능 정보를 효과적으로 예측할 수 있다.
Abstract:
PURPOSE: A diagnosis and treatment method of glioma by checking the location change of proteins is provided to compare the incidence rate at specific location inside the cells, thereby accurately diagnosing the glioma. CONSTITUTION: A diagnosis and treatment method of glioma comprises the following steps: measuring the incidence rate of cell membrane and endoplasmic reticulum of the GDNF receptor alpha 4 in an entity which will be diagnosed; and deciding as the glioma if the incidence rate is higher in the endoplasmic reticulum of the GFRA4 of the entity than the cell membrane. The diagnosis and treatment method of glioma additionally includes a step of deciding the disease as the glioma if the incidence rate is higher in the nucleus of KIF13A or SYT9 protein than in Golgi. The diagnosis and treatment method of glioma additionally includes a step of deciding the disease as the glioma if the incidence rate is higher in the nucleus of RNF138, DLX2, TBX19 or NFRκB protein than in the endoplasmic reticulum.
Abstract:
PURPOSE: A method for predicting a dynamic protein function including the subcellular localization of protein is provided to predict the subcellular location of the protein under stressful conditions by inputting the information of target protein and neighboring protein into a network. CONSTITUTION: A static feature is generated by inputting the static characteristic of target protein(S110). A static network is generated by inputting the interaction information of static protein(S120). A network feature is generated by applying the static characteristic of the target protein and neighboring protein to the static network(S130). A location-feature model is generated by using the static feature and the network feature(S140). A dynamic network is generated(S160). A protein feature is generated by applying the static characteristic and the location information of the target protein to the dynamic network(S170). The location of the target protein is predicted based on the protein feature and the location-feature model(S180).