The technology is ready to be applied and validated in many different areas for research and diagnostic purposes.
Available for licensing and commercial development are methods to optimize sequence-based assays such as microarrays, multiplexed PCR or multiplexed antibody methods. This computational method uses numerical optimization to identify an optimal probe set to be used in an assay for the measurement of a specified set of targets. The method incorporates the sequence information of the target (protein, DNA, RNA or other polymer), the assay characteristics, limits on probe set size and assay probe length in its optimization. The method selectively optimizes the total information provided by the assay within constraints of individual probe performance and coverage of all targets in the target set. For example, the target set of sequences could represent known viral or bacterial pathogens, or splice variants of a single gene. The method selectively identifies sequences within each target sequence with the best individual probe performance and providing the most information. An individual probe may be selected because it provides specific information about a single target (specificity) or because it increases (sensitivity) by providing replicate measurements of a sequence common to several targets.
The method’s software design allows for large (>10,000) target sets and large probe set sizes (2->1,000,000) While current selection criteria involve a time consuming iterative and manual process, the present invention allows for the identification of a quantitatively optimized probe set which balances probe performance criteria and simultaneously optimizes the sensitivity and specificity of the assay for a given set of targets.
The invention has applications in the design of various important assays, such as those based on microarrays, multiplexed PCR and SPR, targeted protein fragment detection, or any sequence-specific binding and detection. It has application where the number of probes to be used in an assay is too large for manual design and review.