Abstract: The present invention provides methods of detecting a nucleic acid analyte in a sample. The present invention further provides a method for assigning a profile of a feature to a nucleic acid. The present invention further provides a computer program product for use in a subject method. The present invention further provides a system for detecting a nucleic acid in a sample; and a system for assigning a profile of a feature to a nucleic acid. The present invention further provides a method for immobilizing a nucleic acid onto an insoluble support; and further provides insoluble support having nucleic acid(s) immobilized thereon. The present invention further provides a method of diagnosing a disorder or condition in an individual, where the method involves use of a subject method for detecting a nucleic acid analyte.

Abstract: Exemplary embodiments of exemplary methods, procedures, computer-accessible medium and systems according to the present disclosure can be provided which can be used for determining token causality. For example, data which comprises token-level time course data and type-level causal relationships can be obtained. In addition, a determination can be made as to whether the type-level causal relationships are instantiated in the token-level time course data, and using a computing arrangement. Further, exemplary significance scores for the causal relationships can be determined based on the determination procedure. It is also possible to determine probabilities associated with the type-level causal relationships using the token-level time course data and a probabilistic temporal model and/or type-level time course data when at least one of the type-level causal relationships have indeterminate truth values.

Abstract: Methods, computer-accessible medium, and systems for generating a genome wide probe map and/or a genome wide haplotype sequence are provided. In particular, a genome wide probe map can be generated by obtaining a plurality of detectable oligonucleotide probes hybridized to at least one double stranded nucleic acid molecule cleaved with at least one restriction enzyme, and detecting the location of the detectable oligonucleotide probes. For example, genome wide haplotype sequence can be generated by analyzing at least one genome wide restriction map in conjunction with at least one genome wide probe map to determine distances between restriction sites of the genome wide restriction map(s) and locations of detectable oligonucleotide probes of the genome wide probe map(s) and defining a consensus map indicating restriction sites based on the genome wide restriction map(s) and/or locations of detectable oligonucleotide probes based on each of the genome wide probe map(s).

Abstract: The present disclosure relates to exemplary embodiments of method, computer-accessible medium, system and software arrangements for, e.g., Cancer Hallmark Automata, a formalism to model the progression of cancers through discrete phenotypes (so-called hallmarks). The precise computational model described herein includes the automatic verification of progression models (e.g., consistency, causal connections, etc.), classification of unreachable or unstable states (e.g., “anti-hallmarks”) and computer-generated (individualized or universal) therapy plans. Exemplary embodiments abstractly model transition timings between hallmarks as well as the effects of drugs and clinical tests, and thus allows formalization of temporal statements about the progression as well as notions of timed therapies. Certain exemplary models discussed herein can be based on hybrid automata (e.g., with multiple clocks), for which relevant verification and planning algorithms exist.

Abstract: The present invention relates to systems, methods, and software arrangements for determining associations between two or more datasets. The systems, methods, and software arrangements used to determine such associations include a determination of a correlation coefficient that incorporates both prior assumptions regarding such datasets and actual information regarding the datasets. The systems, methods, and software arrangements of the present invention can be useful in an analysis of microarray data, including gene expression arrays, to determine correlations between genotypes and phenotypes. Accordingly, the systems, methods, and software arrangements of the present invention may be utilized to determine a genetic basis of complex genetic disorder (e.g. those characterized by the involvement of more than one gene).

Abstract: Exemplary methods, procedures, computer-accessible medium, and systems for base-calling, aligning and polymorphism detection and analysis using raw output from a sequencing platform can be provided. A set of raw outputs can be used to detect polymorphisms in an individual by obtaining a plurality of sequence read data from one or more technologies (e.g., using sequencing-by-synthesis, sequencing-by-ligation, sequencing-by-hybridization, Sanger sequencing, etc.). For example, provided herein are exemplary methods, procedures, computer-accessible medium and systems, which can include and/or be configured for obtaining raw output from a sequencing platform configured to be used for reading fragment(s) of genomes, obtaining reference sequences for the genomes obtained independently from the raw output, and generating a base-call interpretation and/or alignment using the raw output and the reference sequences.

Abstract: Methods, computer-accessible medium, and systems for generating a genome wide probe map and/or a genome wide haplotype sequence are provided. In particular, a genome wide probe map can be generated by obtaining a plurality of detectable oligonucleotide probes hybridized to at least one double stranded nucleic acid molecule cleaved with at least one restriction enzyme, and detecting the location of the detectable oligonucleotide probes.

Abstract: Exemplary embodiments of the present disclosure relate generally to methods, computer-accessible medium and systems for assembling haplotype and/or genotype sequences of at least one genome, which can be based upon, e.g., consistent layouts of short sequence reads and long-range genome related data. For example, a processing arrangement can be configured to perform a procedure including, e.g., obtaining randomly located short sequence reads, using at least one score function in combination with constraints based on, e.g., the long range data, generating a layout of randomly located short sequence reads such that the layout is globally optimal with respect to the score function, obtained through searching coupled with score and constraint dependent pruning to determine the globally optimal layout substantially satisfying the constraints, generating a whole and/or a part of a genome wide haplotype sequence and/or genotype sequence, and converting a globally optimal layout into one or more consensus sequences.

Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.

Abstract: Exemplary embodiments of system, computer-accessible medium and method can be provided for organizing or analyzing at least two sets of data. The sets of data can be organized and/or analyzed by generating a data structure for the sets of data and comparing the data structure for the at least two sets of data. The data structure can be in the form of a phylogenetic-type tree, and at least one of the sets of the data can include time series data.

Abstract: An exemplary embodiment of system, computer-accessible medium and method for comparing a first genome to a second genome. For example, a first genome may be compared to a second genome by building a first library for the first genome and a second library for the second genome, providing a plurality of matches between elements in the first library common to elements in the second library, ranking each match to determine a likelihood of similarity between the common elements in the first and second libraries; and associating matches having a predetermined likelihood. The association may be performed efficiently by a stable marriage procedure.

Abstract: The present invention provides a method for organizing genomic information from multiple organisms. In one embodiment of the invention, phylogenetic trees can be constructed for the organisms. The method of the present invention is termed CAPO, Comparative Analysis and Phylogeny with Optical-Maps. Optical maps of organisms are obtained and phylogeny between the organisms is determined by optical map comparison and bipartite graph matching between the organisms, as, for example, computed by a stable marriage algorithm.

Abstract: Agent-based models (ABMs)/multi-agent systems (MASs) are one of the most widely used modeling-simulation-analysis approaches for understanding the dynamical behavior of complex systems. These models can be often characterized by several parameters with nonlinear interactions which together determine the global system dynamics, usually measured by different conflicting criteria. One problem that can emerge is that of tuning the controllable system parameters at the local level, in order to reach some desirable global behavior. According to one exemplary embodiment t of the present invention, the tuning of an ABM for emergency response planning can be cast as a multi-objective optimization problem (MOOP). Further, the use of multi-objective evolutionary algorithms (MOEAs) and procedures for exploration and optimization of the resultant search space can be utilized. It is possible to employ conventional MOEAs, e.g.

Abstract: Time-course data with an underlying causal structure may appear in a variety of domains, including, e.g., neural spike trains, stock price movements, and gene expression levels. Provided and described herein are methods, procedures, systems, and computer-accessible medium for inferring and/or determining causation in time course data based on temporal logic and algorithms for model checking. For example, according to one exemplary embodiment, the exemplary method can include receiving data associated with particular causal relationships, for each causal relationship, determining average characteristics associated with cause and effects of the causal relationships, and identifying the causal relationships that meet predetermined requirement(s) as a function of the average characteristics so as to generate a causal relationship.

Abstract: A method, system and software arrangement in accordance with an exemplary embodiment of the present invention are provided to extract descriptive narrative from numerical experimental data augmented with ontological controlled vocabulary. One exemplary application of such system, method and software arrangement is in organizing gene-expression time course data in terms of biological processes that may be activated and deactivated as the biological system responds to its normal or perturbed environment. The present invention may also have biological applications to drug-or-vaccine discovery, understanding behavior of a cell in an altered diseased state (e.g., cancer, neuro-degeneration or auto-immune disease, etc.), genetically modifying a natural wild-type organism, genetic-engineering, etc. Other exemplary applications may include understanding neural behavior, market behavior of a population of users interacting on the Internet, etc.

Abstract: The present invention relates to systems, methods and software arrangements for the detection of variations in the copy number of a gene in a genome. These systems, methods and software arrangements are based on a simple prior model that uses a first process generating amplifications and deletions in the genome, and a second process modifying the signal obtained to account for the corrupting noise inherent in the technical methodology used to scan the genome. A Bayesian approach according to the present invention determines, e.g., the most plausible hypothesis of regional changes in the genome and their associated copy number. The systems, methods, and software arrangements can be are framed as optimization problems, in which a score function is minimized. The system, methods and software arrangements may be useful to assist the scientific study, diagnosis and/or treatment of any disease which has a genetic component, including but not limited to cancers and inherited diseases.

Abstract: The present invention relates generally to systems, methods, storage media, and software arrangements for genotyping and/or haplotyping a sequence of polymorphic genetic loci in a deoxyribonucleic acid (DNA) sample or identifying a strain variant from the DNA sample. Exemplary embodiments of systems, methods, storage media, and software arrangements may perform the optimization of the design of one or more microarrays, each containing a set of oligonucleotide probes capable of detecting one or more known genotypes and/or haplotypes at given polymorphic genetic loci or identifying the strain variant, by optimizing the set of oligonucleotides to be incorporated into the microarrays and by optimizing the arrangement of a set of oligonucleotides on the microarrays. The optimization may be achieved through the application of one or more optimization procedures.

Abstract: The present disclosure provides methods of measuring a property of a macromolecule. The methods generally involve applying an empirically learned correction term to a test metric to generate a high-accuracy measurement. The present disclosure further provides a computer program product and a computer system for carrying out a subject method.

Abstract: Disclosed is an analysis method useful in multiplexed hybridization-mediated analysis of polymorphisms, i.e., wherein a labeled nucleic acid of interest (“target”) interacts with two or more pairs of immobilized degenerate capture probes. In one embodiment, one member of each pair has a sequence that is complementary to the normal (“wild-type”) sequence in a designated location of the target, while the other member of each pair has a sequence that is complementary to an anticipated variant (“mutant” or “polymorph”) sequence in that location of the target. These methods permit selection of two or more probe pairs such that, for each pair of probes interacting with a given target strand, interaction of the target with a preferred member of the probe pair is optimized. Also interpreting results obtained by multiplexed hybridization of the target to two or more pairs of probes under conditions permitting competitive hybridization is disclosed.

Abstract: A method and system for determining a feature of a particular pattern are provided. In particular, data records are received, and predetermined patterns that are associated with at least some of the data records are obtained. Using the system and method, particular information is extracted from at least a subset of the received data records, the particular information being indicative of the particular pattern in at least some of the data records. Then, it is determined whether the particular pattern is an unexpected pattern based on the obtained predetermined patterns. In addition, it is possible to classify and reduce data and/or parameters provided in the data records. First, the data records are received. Then, the data records which have at least one particular pattern are classified using a Multivariate Adaptive Regression Splines technique. Thereafter, the data and/or parameters of the classified data records are shrunk using a Stein's Estimator Rule technique.