Disease biomarker screening analysis method, disease biomarker screening analysis platform, server and disease biomarker screening analysis system

Abstract

The invention provides a disease biomarker screening analysis method, a disease biomarker screening analysis platform, a server and a disease biomarker screening analysis system, wherein the disease biomarker screening analysis method comprises the following steps of: receiving an analysis instruction, wherein the analysis instruction includes sample screening conditions and analysis program parameters; obtaining clinical information of samples to be analyzed corresponding to the sample screening conditions according to the sample screening conditions, and obtaining relevant biological information according to the clinical information of the samples to be analyzed; sending the clinical information of the samples to be analyzed, the relevant biological information and the analysis program parameters to the server so as to analyze the clinical information of the samples to be analyzed and the relevant biological information; receiving an analysis result returned by the server, and performing significance inspection on the analysis result; and if the analysis result is non-significant, resetting screening conditions, and performing analysis again until the analysis result is significant. The method provides a platform associating the clinical information with genome information for the genome research aspect, and the great-sample-size gene verification experiment is facilitated.

Description

technical field [0001] The invention relates to the technical field of biological information, in particular to a method, platform, server and system for screening and analyzing disease biomarkers. Background technique [0002] With the continuous development of computer technology and the continuous optimization of statistical algorithms, clinical medical diagnosis data and uncertain ambiguous data in experiments have been gradually analyzed and processed by methods such as probability theory, statistics and decision analysis. Especially after the widespread use of HIS (Hospital Information System, hospital information system) and PACS (Picture Archiving and Communication Systems, image archiving and communication system), these methods have more effectively promoted the progress of clinical diagnosis, treatment efficiency and effect. Now electronic medical records, expert diagnosis and decision-making systems, virtual hospitals, telemedicine and medical education are chang...

AI Technical Summary

Problems solved by technology

Therefore, the relationship between individual phenotype information and disease can only be used, but no further relationship between genes and disease can be found

In addition, most of the current clinical information databases are established and used within a certain range, such as between one or several cooperative hospitals, but they are difficult to share in the entire medical system, which is not conducive to the diagnosis and treatment of diseases based on diverse data. to analyze

Therefore, the reason why the current clinical information database and analysis methods are difficult to maximize is that various clinical observation data are used for medical analysis, which is not conducive to clinical diagnosis, which makes it difficult to improve the efficiency and effect of treatment.

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