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Key protein predicating method based on priori knowledge and network topology characteristics

A key protein and network topology technology, applied in the field of predicting new key proteins based on some known key proteins and biological network topological properties, can solve the problems of high cost and time-consuming chemical experimental methods, and achieve high cost and time-consuming solutions. , to achieve a simple effect

Active Publication Date: 2013-02-27
CENT SOUTH UNIV
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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide a simple method for predicting key proteins based on prior knowledge and network topology characteristics in view of the deficiencies in the prior art. Know the topological closeness of key proteins to predict the criticality of other proteins, solve the problems of expensive and time-consuming chemical experiment methods, and improve the accuracy of key protein prediction

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  • Key protein predicating method based on priori knowledge and network topology characteristics
  • Key protein predicating method based on priori knowledge and network topology characteristics
  • Key protein predicating method based on priori knowledge and network topology characteristics

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Embodiment Construction

[0023] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0024]The most widely studied species is yeast, and there are already a certain number of key yeast proteins determined by experimental means. The present invention downloads the yeast protein interaction network data from the DIP (the database of interacting proteins) database. The interaction data were removed from self-interactions and redundant interactions, and the final protein interaction network consisted of 5093 yeast proteins and 24743 pairs of interactions. The key protein data used in the experiment comes from MIPS (Munich Informationcenter for Protein Sequences), SGD (Saccharomyces Genome Database), DEG (Database of Essential Genes) and SGDP (Saccharomyces Genome Deletion Project) four databases. Through comparison, among the 5093 proteins in the yeast PPI network used in the experiment, a total of 1167 are key proteins, 3591 are...

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Abstract

The invention discloses a key protein predicating method based on priori knowledge and network topology characteristics. Based on the analysis of the topological relation between known key proteins, the close relation between key proteins is found; edge clustering coefficients are taken as parameters for assessing the close degree of two key proteins; and parts of known key proteins and the shared-clustering coefficients of neighbor nodes and the known key proteins are utilized for predicating new key proteins. The key protein predicating method is simple to implement and unknown key proteins can be accurately predicated just according to PPI (protein-protein interaction) information and information of parts of known key proteins, the method is applicable to not only non-weighted PPI networks but also weighted PPI networks, and the problems such as high cost and time wasting of a chemical experiment method are solved.

Description

technical field [0001] The invention relates to the field of prediction of key proteins based on the network level, in particular to a method for predicting new key proteins based on some known key proteins and topological properties of biological networks. Background technique [0002] Protein is an essential component of all cell and tissue structures. It is the executor of physiological functions and the embodiment of life phenomena. Different proteins perform different physiological functions. Among them, there are some proteins whose removal through gene knockout mutation will cause the loss of function of the relevant protein complex and cause the organism to fail to survive. These proteins are called key proteins. Effective prediction of key proteins is of great significance to the study of cell growth regulation processes, and is also of great value to the study of pathogenic biology and drug design. [0003] In the field of biology, experimental methods such as ge...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/18
Inventor 李敏张含会王建新
Owner CENT SOUTH UNIV
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