The University of Tennessee Research Foundation

Other

US Government As Represented by the Secretary of the Army

Tse-Wei Wang

John Douglas Birdwell

David J Icove

Dale V Stansberry

Roger Horn

Mark S Rader

J Douglas Birdwell

Puneet Yadav

Sally P Horn

Jared B Pendleton

Ranajit Chakraborty

John R Flaherty

Xue Ning

Ning Xue

Carl G Sapp

Kenneth H Gilbert

Dale V Stransberry

The present invention provides a method of predicting whether an unknown biological specimen originates from a member of a particular family. The method compares DNA profiles from at least one unknown biological specimen to DNA profiles of more than one family member, which significantly increases the methods' predictive ability. In particular, the invention describes a method of comparing test DNA profiles from unknown biological specimens to a family pedigree comprising target DNA profiles obtained from biological specimens of family members. In one embodiment, a modified Elston Stewart algorithm is used to determine a probability that a genetic relationship exists between at least one unknown biological specimen and the family pedigree.

Methods of associating an unknown biological specimen with a family

Three methods of predicting whether an unknown biological specimen of a missing person originates from a member of a particular family comprise an initial automated decision support (ADS) algorithm for determining a list of relatives of the missing person for DNA typing and which typing technologies of available technologies to use for a listed relative. The ADS algorithm may be implemented on computer apparatus including a processor and an associated memory. The ADS method comprises determining a set of relatives of available family member relatives for DNA typing via a processor from a stored list of family member relatives according to one of a rule base, a table of hierarchically stored relatives developed based on discriminatory power or by calculating the discriminatory power for available family relatives to type. The ADS method may further comprise comparing at least one set of DNA typing data for the unknown biological specimen to DNA typing data from biological specimens from the determined set of relatives; calculating by the processor a likelihood function that the person is related to the family; and outputting a decision whether or not the person is related to the family.

Automated decision support for associating an unknown biological specimen with a family

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic and thermal spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, an evidence tree display showing a target object linked by a pathway to a predicted property comprises a similarity value, a speculation value and a model-based rank.

Method and apparatus for predicting object properties and events using similarity-based information retrieval and modeling

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a machine component or process failure event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a criminal activity and a fraudulent activity event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method utilizes a model comprising application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods.

Analysis of DNA is critical to many applications including identifying perpetrators of crimes based on genetic evidence left at crime scenes. An initial step to analyzing DNA data is detection, identification, and quantization of allele peaks in the DNA data. The invention provides a method and apparatus for accurately and expeditiously performing this initial step by sequentially checking unfitted peaks against various models including a default model, a hybrid peak model, a dual fit model and, in special situations, a narrow fit function and a saturated fit function.

Method and apparatus for allele peak fitting and attribute extraction from DNA sample data

Method and apparatus for determining a metric for use in predicting properties of an unknown specimen belonging to a group of reference specimen electrical devices comprises application of a network analyzer for collecting impedance spectra for the reference specimens and determining centroids and thresholds for the group of reference specimens so that an unknown specimen may be confidently classified as a member of the reference group using the metric. If a trait is stored with the reference group of electrical device specimens, then, the trait may be predictably associated with the unknown specimen along with any traits identified with the unknown specimen associated with the reference group.

Method and apparatus for classifying known specimens and media using spectral properties and identifying unknown specimens and media

The present invention provides at least three methods of predicting whether an unknown biological specimen originates from a member of a particular family. These methods compare DNA profiles from unknown biological specimens to DNA profiles of more than one family member, which significantly increases the methods' identification ability. In particular, the invention describes combining at least a ranked first family member list and a ranked second family member list to create a combined ranked list and identifying the unknown biological specimen as one contained among a list of specimens having the highest combined rankings representing the candidates that are most likely related to the family. A second method encompasses comparing test DNA profiles from unknown biological specimens to a family pedigree comprising target DNA profiles obtained from multiple biological specimens of family members. This method also embodies using a modified Elston Stewart algorithm to determine a pedigree likelihood ratio to rank and identify the test profile of the unknown biological specimen most likely to be the missing person sought after by the corresponding family represented by the family pedigree. A third method encompasses construction of a database or directed graph of discovered or known relationships between biological specimens and comparison to a graph representing a family pedigree to identify portions of the database or directed graph that correspond to portions of the family pedigree, in order to rank or identify one or more unknown biological specimens as most likely related to one or more family pedigrees.

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, a fire event and residual objects may be located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Method and apparatus for predicting properties of a target object comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, one of a process failure event, an intrusion event and a fire event and residual objects may be predicted and located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Method and apparatus for predicting object properties and events using similarity-based information retrieval and model

Method and apparatus for predicting properties of a target object, in particular, one of an origin and a source, comprise application of a search manager for analyzing parameters of a plurality of databases for a plurality of objects, the databases comprising an electrical, electromagnetic, acoustic spectral database (ESD), a micro-body assemblage database (MAD) and a database of image data whereby the databases store data objects containing identifying features, source information and information on site properties and context including time and frequency varying data. The method comprises application of multivariate statistical analysis and principal component analysis in combination with content-based image retrieval for providing two-dimensional attributes of three dimensional objects, for example, via preferential image segmentation using a tree of shapes and to predict further properties of objects by means of k-means clustering and related methods. By way of example, a fire event and residual objects may be located and qualified such that, for example, properties of the residual objects may be qualified, for example, via black body radiation and micro-body databases including charcoal assemblages.

Least Square Deconvolution (LSD) uses quantitative allele peak data, for example, allele peak area, allele peak height and optical density, derived/obtained from a sample containing the DNA of more than one contributor to resolve the best-fit genotype profile of each contributor. The resolution is based on finding the least square fit of the mass ratio coefficients at each locus to come closest to the quantitative allele peak data. Consistent top-ranked mass ratio combinations from each locus can be pooled to form at least one composite DNA profile at a subset of the available loci. The top-ranked DNA profiles can be used to check against the profile of a suspect or be used to search for a matching profile in a DNA database.

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Oak Ridge, TN, United States of America

Tse-Wei Wang