PrimerSelect

PrimerSelect predicts PCR amplification bias to optimize PCR primer design and improve sensitivity and specificity of pathogen detection with DNA microarray integration.

Key Features:

• Robust algorithm for PCR bias prediction: Predicts biases inherent to random PCR-amplification to inform primer selection that minimizes amplification errors.
• Improved primer design: Evaluates target-probe annealing specificity to reduce cross-hybridization and increase primer specificity.
• Integration with microarray technology: Correlates predicted amplification bias with hybridization signals on customized DNA microarray platforms to support pathogen identification.

Scientific Applications:

• Clinical diagnostics: Supports DNA microarray-based genomic sensing for sensitive and specific pathogen detection in clinical specimens.
• Pathogen identification: Aids pathogen identification on microarray platforms and has been used in comparative studies reporting 94% accuracy in identifying pathogens from patient specimens.

Methodology:

Leverages statistical inference on probe recognition signatures to predict and mitigate PCR amplification bias and relates amplification efficiency to hybridization signal for pathogen identity inference.