A particle simulation device comprises: a position information acquisition unit that acquires position information for the particles; a pair setting unit that selects pairs of particles and sets a pair number, on the basis of the position information; a reference information generation unit that generates a matrix from the pair numbers and the particle numbers, and generates reference information for referencing the pair numbers from the particle numbers on the basis of a matrix in which the order of the rows of the matrix are sorted on the basis of the particle numbers; a sum calculation unit that calculates a sum of interaction forces for each particle on the basis of the reference information; and a particle information calculation unit that calculates the position and velocity of the particles on the basis of the sum of interaction forces.

Techniques to identify a mechanism of action of a compound using network dysregulation are disclosed herein. An example method can include selecting at least a first interaction involving at least a first gene, determining a first n-dimensional probability density of gene expression levels for the first gene and one or more genes in a control state, determining a second n-dimensional probability density of gene expression levels for the first gene and one or more genes following treatment using at least one compound, estimating changes between the first probability density and the second probability density, and determining whether the estimated changes are statistically significant.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

A defined peak region residing between about 3.2 and 3.4 ppm of a proton NMR spectrum of an in vitro biosample is electronically evaluated to determine a level of trimethylamine-N-oxide (TMAO). The biosamples may be any suitable biosamples including human serum with a normal biologic range of between about 1-50 M or urine with a normal biologic range of between about 0-1000 M.

The present invention builds and conveys to users in need thereof a Grass Growth Index (GGI) and a Nematode Suitability Index (NSI), to assist the determination of whether and when to administer parasiticides to grazing livestock, such as bovine, ovine and caprine animals. In particular, the invention relates to a computer-implemented method whereby GGI and NSI are calculated based upon both user-supplied information (e.g. grass/forage type and location data) and user-independent information (e.g. weather and environmental condition data associated with the location over time, and grass and nematode growth parameters). Importantly, the disclosed methods provide users with information as to when and where their herds of grazing animals may be at the greatest risk of parasite infestation.

A method for quantifying nucleic acid is provided. The method includes determining a first reference threshold cycle for a first predetermined input quantity for a reference nucleic acid, determining a first target threshold cycle for the first predetermined input quantity for a target nucleic acid, determining a second reference threshold cycle for a second predetermined input quantity for the reference nucleic acid, and determining a second target threshold cycle, by the processor, for the second predetermined input quantity for the target nucleic acid. The method further includes receiving a sample threshold cycle, determining a sample input quantity based on the first and second reference threshold cycle and the first and second target threshold cycle, and displaying the sample input quantity to a user.

The present invention provides methods for identifying bio-molecules with desired properties, or which are most suitable for acquiring such properties, from complex bio-molecule libraries or sets of such libraries. More specifically, some embodiments of the present invention provide methods for building sequence-activity models comprising multiplicative terms and using the models to guide directed evolution. In some embodiments, the sequence-activity models include one or more interaction terms, each of which including an interaction coefficient representing the contribution to activity of two or more defined residues. In some embodiments, the models describe relation between protein or nucleic acid sequences and protein activities. In some embodiments, the present invention also provides methods for preparing sequence-activity models, including but not limited to stepwise addition or subtraction techniques, Bayesian regression, ensemble regression and other methods. The present invention further provides digital systems and software for performing the methods provided herein.

Embodiments are directed to a computer implemented method of assessing a relevancy of a drug to a disease state of a patient. The method includes assessing an impact of the drug on driver genes (DGs) of the disease state of the patient, assessing an impact of the drug on druggable target genes (DTs) of the drug, and assessing the relationship between the DGs and DTs that are in one of a plurality of biological pathways of the disease state of the patient. The method further includes combining the impact of the drug on the DGs, the impact of the drug on the DTs, and the relationship between the DGs and DTs that are in the one of the biological pathways, wherein the combining results in an assessment of the relevancy of the drug to the disease state of the patient.

This disclosure is related to systems and methods for rapid determination of microorganism growth and antimicrobial agent susceptibility and/or resistance.

Described herein are computer-readable storage mediums, methods and systems useful for analyzing samples via mass spectrometry. Aspects described herein include methods for normalizing mass spectrometry data that include providing a reference set of mass spectrometry data obtained from a first external standard sample having one or more isotopic standards, wherein the reference set of mass spectrometry data comprises one or more m/z intensity ratios. Methods described herein are useful for reducing errors based on instrument response and ionization efficiencies and improve reproducibility of data from instrument to instrument and from day to day.