In an embodiment, a method includes loading, from a first database, a representation of an Equipped-Human Reference Architecture (EHRA) model that is based on a human-equipment-task framework. The method further includes, based on indications of polymorphic attributes of at least one of a human, a task, an equipment, and an operational environment as defined by the EHRA model, selected by a user, loading a plurality of properties associated with the received indications from a second database. The method further includes polymorphically adding the plurality of properties to the representation of the EHRA model. The method further includes providing an equipped human system (EHS) solution architecture based on the EHRA model with the plurality of properties by analyzing one or more needs of the human, the task, the equipment, and the operational environment and determining an EHS solution meeting each need. The method further includes updating the EHRA model based on EHS solution architecture.

The present invention provides a method for identifying differential activation of a bisubstrate protein modifying enzyme between samples, comprising: (i) incubating a first sample with x different concentrations of the non-protein substrate of said enzyme, wherein x is 2 or greater than 2; (ii) quantifying modification of a polypeptide in said sample at each of the x different concentrations of the non-protein substrate; (iii) determining the affinity of said enzyme for said non-protein substrate; (iv) repeating steps (i) to (iii) for a second or subsequent sample; and (v) comparing the affinity of said enzyme for said non-protein substrate between said samples;
wherein a difference in affinity of said enzyme for said non-protein substrate between samples is indicative of differential activation of said enzyme between samples. The present invention also provides a method for identifying an in vivo substrate of a bisubstrate protein modifying enzyme.

Provided are methods for identifying differentially represented genes, the method comprising the steps of generating a pool of mutant bacteria by transposon mutagenesis with an activating transposon (Tn.sub.A), wherein the Tn.sub.A comprises a promoter such that transposon insertion into bacterial DNA increases the transcription of a gene at or near the insertion site; growing bacteria from the mutant pool in the presence of different amounts of said antibiotic to produce two or more test cultures; and comparing the distribution of Tn.sub.A insertions between test cultures.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

The present disclosure provides methods for determining the ploidy status of a chromosome in a gestating fetus from genotypic data measured from a mixed sample of DNA comprising DNA from both the mother of the fetus and from the fetus, and optionally from genotypic data from the mother and father. The ploidy state is determined by using a joint distribution model to create a plurality of expected allele distributions for different possible fetal ploidy states given the parental genotypic data, and comparing the expected allelic distributions to the pattern of measured allelic distributions measured in the mixed sample, and choosing the ploidy state whose expected allelic distribution pattern most closely matches the observed allelic distribution pattern. The mixed sample of DNA may be preferentially enriched at a plurality of polymorphic loci in a way that minimizes the allelic bias, for example using massively multiplexed targeted PCR.

Genomic references are structured as a reference graph that represents diploid genotypes in organisms. A path through a series of connected nodes and edges represents a genetic sequence. Genetic variation within a diploid organism is represented by multiple paths through the reference graph. The graph may be transformed into a traversal graph in which a path represents a diploid genotype. Genetic analysis using the traversal graph allows an organism's diploid genotype to be elucidated, e.g., by mapping sequence reads to the reference graph and scoring paths in the traversal graph based on the mapping to determine the path through the traversal graph that best fits the sequence reads.

A computer program product, disposed on a non-transitory computer readable media, for analyzing a biological relevance of a candidate gene to a human phenotype is provided. The product includes computer executable process steps operable to control a computer to receive an input phenotype comprised of a plurality of input human traits and at least one input candidate gene; identify a plurality of disease-linked genes by querying disease-linked gene data and identifying genes causally linked to at least one disease; provide values of a semantic similarity metric for a identified gene set with respect to the input phenotype based on a comparison of human traits linked to each gene of the identified gene set and the input human traits, the identified gene set including genes mechanistically related to the input candidate gene that are included in the identified disease-linked genes; and output a statistical measure indicating whether the values of the semantic similarity metric of the genes of the identified gene set with respect to the input phenotype are greater than the values of the semantic similarity metric of others of the identified disease-linked genes with respect to the input phenotype by a statistically significant amount.

A variant information processing device for processing genetic information includes a processor configured to create variant storage data, from variant information of each of a plurality of target individuals to be processed, where the variant information includes information of variant locus and variant pattern associated with the variant locus. The variant locus corresponds to a portion where the genetic information varies among the plurality of target individuals, the variant pattern corresponds to the genetic information of the portion, and the variant storage data includes an array region with each a first storage region with a fixed bit length and a second storage region with the fixed bit length. The code associated with the variant pattern at each of the variant locus is stored in first storage region or both of the first and second storage regions depending on the length of variant pattern associated with the code.

A software development tool uses a workflow pattern that describes software applications. The tool may provide a solution that can automatically generate a well-architected application without compromising its quality or integrity. The tool may have a Data Notation Architecture (DNA) layer and a Resolution Notation Architecture (RNA) layer Genetic Framework that use a workflow pattern that describes software applications. Models may be identified and linked together using a Polymorphic Relational Path Language (PRPL), which is a scripting language that is designed and optimized to resolve various hierarchy and set theory problems that naturally appear in programming. When targeting the Service Area Architecture Pattern (SAAP), this Genetic Framework may greatly reduce the overall cost of virtually every part of the software development lifecycle.

An online clinical trial enrollment system enables patients to directly input their data for standardized processing. It has the steps of a. a patient-operated device for reading displayed commands and inputting responses; b. a server programmed to archive and process data from a plurality of patients, compare, analyze and aggregate information, perform statistical analysis and produce reports on a viewing screen and paper; c. a new user registration; d. an informed consent with pages of information on the clinical trial and pages for user consent; e. a qualifying questionnaire; f. a genotype upload and transfer with a screen; g. display of optimal clinical trial choice with user compliance question; and h. screens with specific information and more detailed questionnaire.