Systems and methods are provided for processing a melting or dissociation curve of a DNA or other sample, for example, during PCR processing. In some embodiments, detection of the melting point and melting curve behavior can be enhanced by taking a derivative of the curve, and detecting peaks in the differential dissociation curve. In some embodiments, the derivative operation can comprise the use of edge-processing, or other detection algorithms. In some embodiments, the dissociation analysis can comprise removing low-frequency (or pedestal) components of the differential dissociation curve. In some embodiments, the differential dissociation curve can exhibit a smoothed or more regular appearance than the raw detected data.

Determining relative connections between individuals includes: obtaining identification information of a first individual and identification information of a second individual; determining, based at least in part on a relative connections graph, a relative connections path connecting the first individual, the second individual, and at least one additional individual; and outputting information pertaining to the relative connections path.

The present invention belongs to the field of genomics and nucleic acid sequencing. It involves a novel method of sequencing biological material and real-time probabilistic matching of short strings of sequencing information to identify all species present in said biological material. It is related to real-time probabilistic matching of sequence information, and more particular to comparing short strings of a plurality of sequences of single molecule nucleic acids, whether amplified or unamplied, whether chemically synthesized or physically interrogated, as fast as the sequence information is generated and in parallel with continuous sequence information generation or collection.

A method of measuring and calculating (preferably by a computer with output to a user) tGSH (total glutathione very particularly defined) with sample preparation and assay methods that have been confirmed to provide accurate and reliable tGSH and related diagnostic assays in blood or tissue from a patient.

The present invention was made to provide novel methods for detecting DNA and devices therefor. Specifically, the present invention is a method of detecting DNA including the steps of: adding, to an oil, a fluorescently-labeled probe, a DNA intercalator, and a DNA solution containing a target DNA to produce droplets; performing PCR on the droplets; and measuring fluorescence from the fluorescently-labeled probe and fluorescence from the DNA intercalator, wherein the DNA solution has a concentration at which each droplet is produced so as to contain one or less target DNA molecule. In addition, the present invention is a DNA detection device including a droplet production unit, a thermal cycler unit, and a fluorescence detection unit which perform these steps.

Various embodiments perform stable gene analysis of transcriptome sequencing data. In one embodiment, a plurality of datasets each including transcriptome sequencing data are received by a processor. Each of the plurality of datasets includes a plurality of genes and a respective ranking value for each of the plurality of genes. A plurality of rank normalized input datasets is generated based on assigning, for each of the plurality of datasets, a rank to each of the plurality of genes. One or more longest increasing subsequence (LIS) of ranks are identified between each pair of the plurality of rank normalized input datasets. A set of stable genes from the plurality of genes is identified based on each of the one or more LIS of ranks across the plurality of rank normalized input datasets.

Computer-implemented methods for providing improvements in genome-scale metabolic models are described. The methods identify and optimize metabolic flux states that minimize the cost of enzyme production while maximizing a desired cellular phenotype. The computer-implemented methods may maximize cellular phenotypes such as growth (biomass) or production of a metabolite, such as a commercially valuable chemical compound, through the selection of metabolic pathways that maximize these phenotypes while minimizing metabolic costs associated with production of the proteomic constituents of individual metabolic pathways. The computer implemented methods may be useful for computationally designing microbial strains for the production of chemicals.

Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.

Provided is a system which controls information presented to a user referring to contents including a plurality of elements, outputs the contents to an output device, obtains bioinformation of the user at a time when each of the elements included in the contents is output to the output device, calculates an understanding level of the user with respect to each of the elements included in the contents, based on each piece of the obtained bioinformation, determines the understanding type based on the calculated understanding level and a difficulty level indicated by the difficulty level information of the elements of which the understanding level is equal to or lower than a first threshold value, in a case where it is determined that the user does not understand the contents based on the calculated understanding level, and outputs the presented information which corresponds to the determined understanding type to the output device.

The present application includes biomarkers, methods, devices, reagents, systems, and kits for the detection and diagnosis of lung cancer. In one aspect, the application provides biomarkers that can be used alone or in various combinations to diagnose lung cancer or permit the differential diagnosis of pulmonary nodules as benign or malignant. In another aspect, methods are provided for diagnosing lung cancer in an individual, where the methods include detecting, in a biological sample from an individual, at least one biomarker value corresponding to at least one biomarker selected from the group of biomarkers provided in Table 18, Table 20, or Table 21, wherein the individual is classified as having lung cancer, or the likelihood of the individual having lung cancer is determined, based on the at least one biomarker value.