Indeterminate PPI network function module mining method based on fuzzy spectral clustering

Abstract

The invention discloses an indeterminate PPI network function module mining method based on fuzzy spectral clustering. The method comprises the following steps: removing repeated interaction and self-interaction in protein-protein interaction data, measuring the interaction of each group by using an edge clustering coefficient, and constructing an indeterminate protein-protein interaction networkchart; improving the similarity measure of the spectral clustering algorithm by using popular distance and the topological properties of the protein network, and further adopting the spectral clustering algorithm to complete preprocessing on protein-protein interaction data; selecting an initial clustering center by using a DPCS strategy, based on the initial clustering center, using a fuzzy C-mean value algorithm to constantly update a clustering center and degree of membership, and then realizing the mining of a protein-protein interaction function module; filtering the mined protein-proteininteraction function module by using the edge expected density of an edge clustering coefficient fused by expected density; and outputting and predicting the mined protein-protein interaction function module.

Description

technical field [0001] The present disclosure relates to the field of systems biology, in particular to a method for mining uncertain PPI network function modules based on fuzzy spectral clustering. Background technique [0002] The proteome is a whole that changes dynamically in space and time, and its function is often manifested through the interaction between proteins or nucleic acids. This interaction exists in the life activities of cells in the body and crosses each other to form proteins Interaction (protein-protein interaction, PPI) network. In a PPI network, the collection of proteins that complete a specific molecular process through interaction in different temporal and spatial stages is called a protein functional module. The mining of functional modules can not only understand the functional organization structure of cells and the way to perform physiological functions, but also help people understand various biological processes, reveal the mechanism of disea...

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Problems solved by technology

However, how to effectively construct an uncertain PPI network, how to overcome the shortcomings of the spectral clustering fusion fuzzy C-means algorithm, which is sensitive to scale parameters, cluster centers, and cluster numbers, has low accuracy, low sensitivity, and low execution efficiency. many challenges remain

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