Gene-Symptom Graph Decision Support for Standardized Phenotyping
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Solution Overview
Problem
Current phenotyping practices in precision medicine suffer from inconsistent and heterogeneous descriptions of symptoms, leading to challenges in accurately identifying genes associated with diseases due to fuzzy matching in medical records.
Innovation Solution
A device and method that utilizes a gene-phenotype matrix to calculate the probability of gene-symptom associations, incorporating correction vectors and normalization weights, and employs graph-based models to standardize phenotyping and identify the most likely genes associated with observed symptoms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If physicians use standardized ontology descriptions for phenotyping, then phenotyping consistency should improve, but in practice heterogeneous and inconsistent symptom descriptions persist
Solution Approach 1:
The patent introduces a symptom-symptom association atlas as an intermediary structure that mediates between heterogeneous clinical descriptions and standardized gene associations. The atlas translates diverse symptom reports into standardized phenotype terms through learned associations, enabling consistent phenotyping while maintaining accuracy in gene identification.
Solution Approach 2:
The patent changes the parameter representation from direct symptom-gene associations to symptom-symptom associations through the atlas. By transforming the association space and introducing a new representation dimension, the system achieves both consistency in phenotyping and accuracy in gene identification.
2Productivity
If existing algorithms use ontology structure to extract symptom-gene associations, then computational efficiency improves, but phenotyping heterogeneity remains unaddressed
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing the symptom-symptom association atlas before actual gene identification tasks. This pre-computed atlas captures heterogeneous phenotyping patterns and enables fast querying during diagnosis, achieving both computational efficiency and adaptability to diverse clinical descriptions.
3Measurement precision
If clinical data is standardized using HPO ontology, then data comparability improves, but fuzzy matching in medical records persists
Solution Approach 1:
The patent implements feedback mechanisms where the symptom-symptom association atlas continuously refines phenotype mappings based on observed clinical data patterns. This feedback loop corrects fuzzy matching errors and maintains high information accuracy while preserving standardized ontology structure.
Data Source
AI summary
A computer-implemented method for decision support of a user to standardize phenotyping in genomic analysis of a subject, wherein the method includes: receiving a list of symptoms having at least one symptom observed for the subject; receiving a first graph having nodes and weighted links; receiving a second graph being previously obtained applying a matrix factorization to a gene-symptom matrix; and outputting at least one gene associated to the list of symptoms based on the first graph and on the second graph.