METHOD AND APPARATUS FOR ANALYZING HYBRIDIZED BIOCHIP PATTERNS USING RESONANCE INTERACTIONS EMPLOYING QUANTUM EXPRESSOR FUNCTIONS

Patent №

US 6,136,541

Granted

2000-10-24

Filed 1999

Owner

VIALOGY CORP.

Lab

AI components

3

ml · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09253789

A technique is described for identifying mutations, if any, present in a biological sample, from a pre-selected set of known mutations. The method can be applied to DNA, RNA and peptide nucleic acid (PNA) microarrays. The method analyzes a dot spectrogram representative of quantized hybridization activity of oligonucleotides in the sample to identify the mutations. In accordance with the method, a resonance pattern is generated which is representative of nonlinear resonances between a stimulus pattern associated with the set of known mutations and the dot spectrogram. The resonance pattern is interpreted to a yield a set of confirmed mutations by comparing resonances found therein with predetermined resonances expected for the selected set of mutations. In a particular example, the resonance pattern is generated by iteratively processing the dot spectrogram by performing a convergent reverberation to yield a resonance pattern representative of resonances between a predetermined set of selected Quantum Expressor Functions and the dot spectrogram until a predetermined degree of convergence is achieved between the resonances found in the resonance pattern and resonances expected for the set of mutations. The resonance pattern is analyzed to a yield a set of confirmed mutations by mapping the confirmed mutations to known diseases associated with the pre-selected set of known mutations to identify diseases, if any, indicated by the biological sample. By exploiting a resonant interaction, mutation signatures may be robustly identified even in circumstances involving low signal to noise ratios or, in some cases, negative signal to noise ratios.

Machine learningVisionAI hardwareG16B 25/00B82Y 5/00B82Y 10/00G16B 25/10G16B 40/10G16B 40/00

AI classification

AI hardware0.99
Machine learning0.80
Vision0.70
Knowledge representation0.34
Evolutionary computation0.02
Natural language0.00
Planning0.00
Speech0.00

Ownership

VIALOGY CORP.

assignment · 99320525

Assignors

GULATI, SANDEEP

On an employer assignment, the assignors are typically the inventors.

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