Syracuse University

Src Corporation

William Ryon McKay

Jonathan David Adelman

Mary F Swartz

Jacquelyn Lillis

Katherine Lawson

The present invention relates to a method and system for classifying high-resolution melt ('HRM') curves, and, more specifically, to a method and system for classifying HRM curves by genotype where the curves are represented by a mathematical function with varying coefficient values.

High-resolution melt curve classification using neural networks

A method and system for geolocation. The method and system determines the geographic history of a target of interest (i.e., the probability that a sample of interest passed though a defined location) given a combination of spatially attributable input data and weighing distributions, and modifying the probability for each possible location using the equation where P(x) is the probability that the sample of interest passes through a given geographic location X, nis the total number of possible legal travel routes for the sample of interest, nis the number of legal travel routes including location X, k is the travel route's cardinality, and w(k) is the assigned weight for cardinality k from the user-defined weighting function.

Combinatorics method for probabilistic geolocation

A method for detecting and identifying nucleic acid tags. A nucleic acid tag comprising a nucleotide-support platform attached to a nucleic acid molecule is created or selected and then immobilized on or in an item, or seeded within an area of interest. Samples are obtained from the surface of an item that has potentially been labeled, and an initial screen is conducted using universal primers to determine which samples contain nucleic acid tag. A multiplex screen is conducted on samples testing positive for nucleic acid tag in order to identify which of a plurality of nucleic acid tags are present on or in the item of interest.

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East Syracuse, NY, United States of America

William Ryon McKay