Nucleic Acid Host Prediction Model for Accurate Oligonucleotide Design

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Solution Overview

Problem

Existing molecular diagnostic technologies face challenges in accurately designing oligonucleotides for detecting target nucleic acid molecules due to inaccuracies in nucleic acid sequence information, particularly when host entity information is unreliable, leading to reduced detection accuracy and inefficiency in molecular diagnostic reagents.

Innovation Solution

A method using a computer-implemented model to accurately assume an organism or host from a given nucleic acid sequence, employing a pre-trained model fine-tuned with semi-supervised learning and tokenization, enabling accurate organism or host identification even with limited labeled data, and ensuring correct information for molecular diagnostic reagent development.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If existing molecular diagnostic technologies use nucleic acid sequence information for detecting target nucleic acid molecules, then detection capability is provided, but detection accuracy deteriorates when host entity information is unreliable

Engineering Contradiction:

Improvedetection accuracyVSAvoidhost entity information reliability

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent replaces traditional mechanical/database-based sequence verification with an AI-based assumption model that uses neural networks to predict and verify host entity information from nucleic acid sequences, enabling automatic correction of unreliable data

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system incorporates feedback mechanisms where the assumption model continuously refines its predictions by comparing predicted host information against the nucleic acid sequence data, allowing iterative improvement of accuracy

Inventive Principle:

Principle #23Feedback

2Productivity

If molecular diagnostic reagents are developed using inaccurate nucleic acid sequence information, then reagent development process is simplified, but oligonucleotide design efficiency deteriorates

Engineering Contradiction:

Improveoligonucleotide design efficiencyVSAvoidinformation verification complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The assumption model performs self-verification by automatically checking and correcting nucleic acid sequence information against learned patterns, enabling the system to self-correct errors without external intervention

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary verification of nucleic acid sequence information against the assumption model before using it for oligonucleotide design, preventing errors from propagating through the development process

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20260004878A1Method for assuming organism or host, method for obtaining model for assuming organism or host, and computer device for performing the same

Publication Date: 2026.01.01 SEEGENE INC

AI summary

Proposed is a computer-implemented method performed by a computer device using a memory, a processor, and one or more programs stored in the memory and configured to be executed by the processor. The method may include accessing an assumption model obtained by fine-tuning a pre-learned model, and providing a nucleic acid sequence to the assumption model. The method may also include assuming an organism carrying the nucleic acid sequence or a host of the organism from the assumption model.