Macromolecule Sequencing Noise Reduction via Cross-Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing serial physical property sequencing methods for DNA and macromolecules are susceptible to significant noise sources, making them costly and inefficient, particularly in nanopore and scanning tunneling microscopy techniques, which hinder accurate and affordable genome sequencing.
Innovation Solution
The implementation of oversampling and cross-correlation techniques to reduce noise in sequencing data by determining signal values for macromolecules, specifically by cross-correlating multiple measured signals with associated time data to eliminate noise not in the same frequency and phase as the systematic signal, thereby increasing the signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If serial physical property sequencing methods are used for DNA and macromolecule sequencing, then sequencing capability is achieved, but noise significantly degrades measurement precision
Solution Approach 1:
The patent applies periodic action by performing multiple sequential measurements of the same physical property at different time points. The method collects a series of measurements over time and uses cross-correlation analysis to identify periodic signal patterns while filtering out random noise, thereby improving sequencing accuracy without requiring additional hardware modifications.
2Reliability
If multiple measured signals are collected to improve signal-to-noise ratio, then sequencing reliability is enhanced, but data processing complexity increases
Solution Approach 1:
The patent replaces complex hardware systems with computational methods. Instead of using multiple complex measurement devices or sophisticated hardware filtering systems, the invention collects multiple signals from simpler measurements and uses cross-correlation algorithms to extract the true signal from noise, reducing hardware complexity while maintaining reliability.
3Measurement precision
If cross-correlation techniques are applied to reduce noise, then signal-to-noise ratio is improved, but computational time increases
Solution Approach 1:
The patent applies preliminary action by performing optimizations and preprocessing steps before the main cross-correlation computation. The method includes pre-processing the measurement data to identify and exclude obviously erroneous readings, and optimizing the correlation calculation algorithm to reduce computational overhead, thereby minimizing time loss while maintaining precision improvement.
Data Source
AI summary
Methods, systems, and devices are disclosed for processing macromolecule sequencing data with substantial noise reduction. In one aspect, a method for reducing noise in a sequential measurement of a macromolecule comprising serial subunits includes cross-correlating multiple measured signals of a physical property of subunits of interest of the macromolecule, the multiple measured signals including the time data associated with the measurement of the signal, to remove or at least reduce signal noise that is not in the same frequency and in phase with the systematic signal contribution of the measured signals.