A Semantic Density-Based Method for Identification of Protein Network Complexes

A protein network and semantic density technology, applied in the field of data mining, can solve the problem of modularity with decomposition limit and increase algorithm time complexity, and achieve the effect of high clustering result accuracy, low time consumption, and low algorithm time complexity.

Inactive Publication Date: 2018-02-16
XIAN UNIV OF TECH
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Problems solved by technology

However, the evaluation function of the network structure often has certain limitations. For example, the modularity adopted by the hierarchical method has the problem of decomposition limit.
Moreover, the calculation of the global optimization function may increase the time complexity of the algorithm

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  • A Semantic Density-Based Method for Identification of Protein Network Complexes
  • A Semantic Density-Based Method for Identification of Protein Network Complexes
  • A Semantic Density-Based Method for Identification of Protein Network Complexes

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Embodiment Construction

[0043] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0044] Related concepts and definitions involved in a protein network complex recognition method based on semantic density of the present invention are as follows:

[0045] Gene Ontology database (Gene Ontology, GO) is a large-scale biological information database, and its goal is to unify the expression of all biological genes and protein properties. GO collects biological attributes as well as biochemical attributes to describe the function of the corresponding protein or its location in the cell. All properties are grouped into three categories: biological process, molecular function, and cellular component, abbreviated as P, F, and C, respectively. As an ontology, GO contains two semantic relations, namely "is_a" and "part_of". The directed acyclic graph (DAG) in the data structure is usually used to represent GO. The nodes in the graph...

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Abstract

The invention discloses a method for identifying protein network complexes based on semantic density, which is specifically implemented according to the following steps: for a weightless protein interaction network data set, search for the attributes of all proteins in the network data set in the gene ontology database GO; Based on the search results, a semantic similarity calculation method based on gene ontology is used to calculate the similarity between the connected proteins in the network dataset; according to the obtained similarity results, the given protein interaction network dataset is transformed into is a weighted, undirected network dataset, where nodes represent proteins, edges represent interactions between proteins, and the similarity between proteins is the weight of the edges; protein complexes can be identified from the protein interaction network, and The recognition accuracy is higher and the time complexity is lower.

Description

technical field [0001] The invention belongs to the technical field of data mining methods, and relates to a method for identifying protein network complexes based on semantic density. Background technique [0002] There has been a long history of empirical research and theoretical simulation of complex networks, and many related techniques and methods derived from statistical physics and applied mathematics have been proposed. The concept of system networking has also been successfully applied to related research in molecular biology. Proteins in biological systems interact with each other to achieve a variety of molecular biological functions, and these interactions are referred to as PPIs (Protein-Protein Interactions). A biological system composed of proteins and interactions can be formally described as an undirected graph, that is, protein interaction network (PPInetworks), protein network for short. In protein networks, each node represents a protein, and edges repr...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/18
Inventor 周红芳段文聪郭杰王心怡何馨依刘杰李锦
Owner XIAN UNIV OF TECH
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