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Published on: September 5, 2019
A dual Kalman filter for parameter-state estimation in real-time DNA microarrays
Summary
This study introduces a dual Kalman filter to estimate target amounts using early binding kinetics from real-time DNA microarrays. The method efficiently quantifies analytes based on initial binding reactions.
Area of Science:
- Biotechnology
- Analytical Chemistry
- Signal Processing
Background:
- Affinity-based biosensors utilize molecular recognition for analyte detection.
- Real-time DNA microarrays capture dynamic binding events over time.
Purpose of the Study:
- To develop a method for estimating analyte (target) amounts using early kinetic data from affinity biosensors.
- To improve the efficiency of analyte quantification in real-time binding assays.
Main Methods:
- Studied the estimation of target amounts based on the early kinetics of the target-probe binding reaction.
- Proposed and evaluated a dual Kalman filter for parameter-state estimation.
Main Results:
- Computational studies demonstrated the efficacy of the proposed dual Kalman filter.
- The method successfully estimates analyte amounts from early binding reaction kinetics.
Conclusions:
- The dual Kalman filter is an effective tool for real-time analyte quantification in affinity biosensors.
- Early kinetic analysis combined with advanced filtering offers efficient biosensing.
