Precision medicine knowledge search system and implementation method based on multi-omics variation characteristics of cases

Abstract

The invention discloses a precise medical knowledge searching system and achievement method based on a case multi-hosphoproteomics variation feature. The system comprises a precise medical knowledge library, an optimizable matching algorithm, an appraisal algorithm of the matching algorithm, and the like. Precise medical knowledge searching is achieved through steps of building a multi-precision medical knowledge library based on a multi-hosphoproteomics variation-intervening response correlation model, extracting the multi-hosphoproteomics variation feature of a new case, building the matching algorithm between the new case and the model to generate an analysis report of a case matching system, renewing data in the knowledge library, and conducting self-evolution on the matching algorithm. The precise medical knowledge searching system is wide in searching range, and correlation models under different observation dimensions can be retrieved. In the precise medical knowledge searching system and achievement method based on the case multi-hosphoproteomics variation feature, the correlation between know hosphoproteomics variation and intervening responses is systematically integrated, by defining a generalized multi-hosphoproteomics variation-intervening response correlation model type framework, the intervening responses information and hosphoproteomics variation information from different levels and sources are integrated into one knowledge library.

Description

technical field [0001] The invention belongs to the field of medical and health industries, and relates to a method for realizing a precision medical knowledge search system, specifically, a method for realizing a precision medical knowledge search system based on multi-omic variation characteristics of cases. Background technique [0002] Precision medicine relies on the classification of biomarkers for disease risk, prognosis, and treatment response. The rapid development of omics technology has greatly enriched the number of biomarkers at the molecular level, providing a more comprehensive and detailed judgment basis for disease diagnosis, judgment of disease staging, or evaluation of the safety and effectiveness of new therapies in the target population. [0003] Currently, the association information of "molecular level markers or pathological variation characteristics-intervention response (including drug response)" can be mainly obtained from several channels such as ...

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Problems solved by technology

Therefore, the current situation that different sources and different types of related information are mixed and indistinguishable has increased the difficulty for many clinical workers in interpreting the physiological significance of omics variation features and utilizing the clinical value.

[0004] In addition, the integration and clinical transformation of omics data also need to consider the issues of data stability, experimental platforms (such as different laboratories or institutions), observation scales (such as cell line level, tissue level, individual level, etc.), observation methods ( Such as transcriptome level, proteome level, or genome level, etc.), observation methods (such as single nucleotide polymorphism chips, next-generation sequencing technology, etc.) and other factors may cause instability in the observed behavior of the same biomarker

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