Drug susceptibility prediction method based on multi-similarity network

Abstract

The present invention discloses a drug susceptibility prediction method based on a multi-similarity network. The method comprises the steps of: employing drug structure information to construct a drugsimilarity network, employing cell line gene expression profile data to construct a cell line similarity network after gene screening, and calculating a gene similarity network according to protein structure information; on this basis, establishing an association relation among drugs, the cell line and the genes, and performing three random walk in multiple networks formed by the constructed drugsimilarity network, the cell line similarity network and the gene similarity network to predict the drug susceptibility. On the basis of simpleness and practicability, the drug susceptibility prediction method based on a multi-similarity network can improve the drug susceptibility identification accuracy and can provide important reference for researchers to perform drug design.

Description

technical field [0001] The invention relates to the technical field of biomedicine, in particular to a drug sensitivity prediction method based on a multi-similarity network. Background technique [0002] Over the past two decades, substantial improvements in high-throughput analytical techniques have raised expectations for personalized or precision medicine to become the future paradigm of medical science. Patients with the same cancer may respond differently to specific drug treatments. Personalized medicine hopes to understand the cause of a specific patient's cancer at the molecular level, and then tailor treatment to address the patient's cancer. Compared with chemotherapy-based monotherapy approaches, personalized medicine looks at tumor response based on established molecular profiles of cancer cells to overcome some of the limitations associated with conventional symptom-oriented disease diagnosis and treatment. The most important step in personalized medicine is t...

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Problems solved by technology

In fact, this two-layer network-based drug sensitivity prediction experiment is to mine the influence of drugs and cell lines on drug sensitivity, but this method does not take into account the drug similarity network and the similarity network of cell lines It has the characteristics of a biological network, so it cannot accurately predict drug sensitivity

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