Abstract:
Provided is a method of identifying a candidate gene for a genetic disease includes obtaining a disease network, disease-gene association information, and a gene network, obtaining a single nucleotide polymorphism (SNP) network based on intra-relation data between a plurality of SNPs, and inter-relation data between genes and SNPs, creating a disease-gene-SNP multilayered network based on the disease network, the disease-gene association information, the gene network, the SNP network, and the interrelation data between genes and SNPs, and identifying a candidate gene for a genetic disease using the multilayered network.
Abstract:
Provided is a method of visualizing a plurality of nodes respectively including a plurality of variable values for a data object. The method includes: allocating a predetermined upper limit value and a predetermined lower limit value for each of a plurality of variables to vertices of a three-dimensional polygon facing each other; respectively determining partial positions related to the variables for the nodes based on the upper limit value and the lower limit value for each of the variables, a maximum variable value and a minimum variable value for each variable from among variable values of the nodes, and the variable values of the nodes; respectively determining final positions of the nodes in the three-dimensional polygon based on the determined partial positions; and arranging the nodes in the three-dimensional polygon according to the determined final positions.
Abstract:
Disclosed is a method of providing a disease co-occurrence probability including (a) receiving a disease network in which respective diseases are shown as nodes and a correlation between diseases is shown as an edge between the nodes and (b) calculating, when at least one disease is given, a probability of an occurrence of another disease in addition to the given disease, the corresponding disease which accompanies the given disease, from the disease network.
Abstract:
A method of scoring suspects in a criminal case includes: obtaining a case network including a plurality of case nodes corresponding to a plurality of cases and a plurality of edges connecting different case nodes; obtaining a people network including a plurality of person nodes corresponding to a plurality of people and a plurality of edges connecting different person nodes, constructing a crime network connecting the case network and the people network through a case-person edge based on association information between a case and a person, and scoring candidate suspects using the crime network when information about a new case is obtained.