Abstract: The present disclosure provides methods and systems for determining and/or characterizing one or more haplotypes and/or phasing of haplotypes in a nucleic acid sample. In particular, the disclosure provides methods for determining a haplotype and/or phasing of haplotypes in a nucleic acid sample by incorporating synthetic polymorphisms into fragments of a nucleic acid sample and utilizing the synthetic polymorphisms in determining one or more haplotypes and/or phasing of haplotypes.

Abstract: Direct targeted sequencing (DTS) methods and a hidden Markov model (HMM) can be used to call the copy number of a segment of interest within a region of interest. Described herein are methods for calling a copy number variant or a copy number variant abnormality using an HMM, and methods for determining a copy number based on a copy number likelihood model, in a test sequencing library that has be sequenced using DTS methods. Also described herein are methods for determining a copy number of a segment, including accounting for spurious capture probes that may arise from the DTS methods.

Abstract: The present disclosure relates to methods of characterizing disease. In particular, this invention relates to methods for selecting a treatment, treating, and predicting survival time in subjects suffering from sepsis, based on the characterization of genes associated with a reactive oxygen species (ROS) molecular signature.

Abstract: Approaches provide for machine learning or training algorithms that apply modifications to models based on a type of data obtained, including, for example, producer-specific management practice data, genetic data, among other such data. The animal-centric models can be configured to, for example, quantify gas emissions (e.g., greenhouse gas emissions) that an animal may be expected to emit over a period of time, including, for example, over the animal's lifetime. The emissions in certain embodiments can further enable the certification of emissions for individual animals.

Abstract: A data processing system configured for computer visualization of drugs for drug interaction information retrieval is disclosed. For each of multiple different substances and using a camera within the mobile or other computing device, imagery of at least one external characteristic of a physical body of the substance is acquired. An identity of each of the multiple different substances is determined based upon the at least one external characteristic from the acquired imagery. Drug interaction data is retrieved for each of the multiple different substances using the determined identities. Drug interaction data for at least one of the multiple different substances is correlated with at least one other of the multiple different substances. At least one generic substance and/or cost information of at least one of the multiple different substances is identified. The correlated drug interaction data, the at least one generic substance, and/or the cost information are displayed.

Abstract: Determination of a frequency distribution of nucleotide sequence variants—differing from a nucleotide reference by at least one intermediate part—of a sample is disclosed. A reference set of sequence read data is generated by performing a plurality of reference sequence reads (each having a read start site, RSS) for each sequence reference variant of a reference variant list. It is determined (for each RSS and for the intermediate part of each sequence reference variant) whether the intermediate part is detectable by corresponding reference sequence read. A sample set of sequence read data is generated by performing sample sequence reads for the sample, and a total number of occurrences in the sample set is determined for each RSS and for the intermediate part of each sequence reference variant. The frequency distribution of the plurality of nucleotide sequence variants is determined based on the number of occurrences determined for an RSS where the intermediate part is detectable.

Abstract: We describe a system and a method that ascertains the strengths of links between pairs of biological sequence variants, by determining numerical link distances that measure the similarity of the molecular phenotypes of the variants. The link distances may be used to associate knowledge about labeled variants to other variants and to prioritize the other variants for subsequent analysis or interpretation. The molecular phenotypes are determined using a neural network, called a molecular phenotype neural network, and may include numerical or descriptive attributes, such as those describing protein-DNA interactions, protein-RNA interactions, protein-protein interactions, splicing patterns, polyadenylation patterns, and microRNA-RNA interactions. Linked genetic variants may be used to ascertain pathogenicity in genetic testing, to identify drug targets, to identify patients that respond similarly to a drug, to ascertain health risks, or to connect patients that have similar molecular phenotypes.

Abstract: Measurement of circulating ST2 and natriuretic peptide (e.g., NT-proBNP) concentrations is useful for the prognostic evaluation of subjects, in particular for the prediction of adverse clinical outcomes, e.g., mortality, transplantation, and heart failure.

Abstract: A method for predicting a likelihood of infection in a set of similarly sourced plant products is disclosed. A subset of plant products is selected from the set of plant products. For each plant product in the subset, a level of expression of one or more infection biomarkers, and optionally a level of expression of one more housekeeping biomarkers, are determined. A set of biomarker expression statistics for the subset of plant products is determined based on the determined levels of expression of the one or more infection biomarkers and optionally the levels of expression of the one or more housekeeping biomarkers for each plant product in the subset. A likelihood of infection in the set of plant products is then predicted based at least in part on the determined set of biomarker expression statistics for the subset of plant products.

Abstract: Displaying a comparison of genotypic information between relatives is disclosed, including receiving an indication that a first individual is a grandparent, receiving an indication that a second individual is a grandchild of the first individual, comparing the genotypic information of the first individual and the second individual and calculating a similarity score, and displaying an indication of the similarity score graphically using colors.

Abstract: Embodiments include methods, systems, and computer program products for analyzing genomic data. Aspects include receiving genomic data for an organism, sample phenotypes, and a plurality of gene sets. Aspects include, for each of the gene sets, determining a set of genes G corresponding to genes in the gene set and a set of genes G? corresponding to genes outside the gene set for the phenotypes R and R?. Aspects also include determining a set of mutated genes M and a set of non-mutated genes M? for R and R? and a mutation enrichment score. Aspects also include determining a set of differentiated genes D a set of non-differentiated genes D? for R and R?. Aspects also include identifying an enriched gene set GE based at least in part upon the mutation enrichment score and the differentiation enrichment score.

Abstract: Methods are provided for analyzing one or more genetic samples, comprising procuring one or more genetic samples comprising genetic material from one or more individuals and sequencing the genetic material using non-targeted, ultra-low coverage sequencing to obtain genetic information for individual associated with the one or more genetic samples. Personal and genetic information associated with the individuals is stored in a database for retrieval and manipulation.

Abstract: An insulin delivery supervisor (IDS) with a safety analysis and supervision function that can reside between the insulin request and the insulin delivery and can intercept any excessive insulin requests before the insulin was delivered. The IDS can be implemented in any system based on insulin pump or pen and will work with either SMBG or CGM modes of blood glucose monitoring.

Abstract: A method for analyzing sample cells reacting with at least one specific marker, includes providing a reference sample and an active sample and providing a set (E+) of cells declared positive from among the active sample cells. The method further includes determining a vector coefficient (?) from the active sample and from the set (E+) and determining at least one set of positive cells in the reference sample as a function of the vector coefficient (?). A rate of false positives (?) is calculated in the reference sample from the number of positive cells of the reference sample.

Abstract: A system and method for converting static/still medical images of a particular patient into dynamic and interactive images interacting with medical tools including medical devices by coupling a model of tissue dynamics and tool characteristics to the patient specific imagery for simulating a medical procedure in an accurate and dynamic manner by coupling a model of tissue dynamics to patient specific imagery for simulating cerebral aneurysm clipping surgery.

Abstract: A method for determining false positives calls in a biological data plot is provided. The method includes identifying a first data cluster as non-amplification data points within the biological data plot and identifying a second data cluster as wild-type positives within the biological data plot. The method further includes estimating a position in the biological data plot of a center of the first and second data clusters. The method further includes determining, for each data point within the first data cluster, a probability of belonging to the first data cluster and determining, for each data point within the second data cluster, a probability of belonging to the second data cluster. The method includes applying a probability threshold for each data point within the first and second data cluster to identify false positives.

Abstract: Methods and systems for characterizing two or more nucleic acids in a sample. The method can include the steps of providing a hybrid machine learning approach that enables rapid and automated deconvolution of DNA mixtures of multiple contributors. The input is analyzed by an expert system which is implemented in the form of a rule set. The rule set establishes requirements based on expectations on the biology and methods used. The methods and systems also include a machine learning algorithm that is either incorporated into the expert system, or utilizes the output of the expert system for analysis. The machine learning algorithm can be any of a variety of different algorithms or combinations of algorithms used to perform classification in a complex data environment.

Abstract: Apparatuses and methods are disclosed for comparing a first biosequence string with a second biosequence string to assess similarity between those biosequence strings. For example, a field programmable gate array (FPGA) can be used to (1) detect substrings of the second biosequence string that are matches to substrings of the first biosequence string, and (2) map the detected substrings of the second biosequence string to corresponding positions in the first biosequence string where the detected substrings are located based on a data structure that links substrings of the first biosequence string to positions in the first biosequence string where the substrings of the first biosequence string are located. These operations can be used to seed an alignment between the first and second biosequence strings that permits comparisons to be performed over longer substrings of the first and second biosequence strings so that similarities between those longer substrings can be quantified.

Abstract: Databases and data processing systems for use with a network-based personal genetics services platform may include member information pertaining to a plurality of members of the network-based personal genetics services platform. The member information may include genetic information, family history information, environmental information, and phenotype information of the plurality of members. A data processing system may determine, based at least in part on the member information, a model for predicting a phenotype from genetic information, family history information, and environmental information, wherein determining the model includes training the model using the member information pertaining to a set of the plurality of members.

Abstract: A computer-implemented method of preparing a set of differentially informative methylated positions (DIMPs) or differentially informative methylated regions (DIMRs) from a sample methylome of an animal or plant having a phenotypic characteristic different from a wild-type of the same species of animal or plant, and the characteristic is associate with differences in methylation of the genome, comprises: providing a computer with the sample methylome, and a reference methylome of the wild-type of the same species of animal or plant; calculating with the computer a divergence between a plurality of cytosine positions of the sample methylome and the reference methylome; and selecting with the computer a set of DIMPs or DIMRs. Each DIMP or DIMR is selected based on an approximation of the energy required to produce the divergence between methylation levels of the plurality of cytosine positions of the sample methylome as compared to the wild-type methylome.