Methods, systems, or computer-readable media are provided for (A) estimating the presence of, or the levels of, analytes in biological samples, (B) estimating characteristics of a condition based on biological samples (C) training a model to estimate a presence of analytes in a biological sample, (D) identifying and evaluating the effectiveness of a treatment for a subject, (E) identifying characteristics of a condition directly based on data obtained from a sample of a subject, and (F) providing a recurring treatment for a subject based on analysis of subject samples.

A data processing system includes an original data storage part (2) that stores original data of a three-dimensional chromatogram including chromatogram data and a spectrum acquired by chromatography analysis, an arithmetic processor (4) configured to execute peak estimation processing of estimating peaks included in a peak waveform portion of the original data stored in the original data storage part by repeating a component estimation step of estimating a three-dimensional chromatogram of one peak component included in the peak waveform portion until synthesis data obtained by synthesizing three-dimensional chromatograms of all estimated peak components of which three-dimensional chromatograms are estimated in the component estimation step approximates the original data, and a maximum number storage part (6) that stores a maximum number of the estimated peak components. The arithmetic processor (4) is configured to end the peak estimation processing regardless of situation of an approximation of the synthesized data with respect to the original data when the number of the estimated peak components reaches the maximum number.

Techniques and apparatus for information assessment processes are described. In one embodiment, for example, a computer-implemented method for performing a review-by-exception process may include, via one or more processors of a computing device, accessing chromatography information generated via analyzing a sample using a mass spectrometry system, the chromatography information comprising at least one peak and at least one peak attribute for the at least one peak, determining posterior probability information for the chromatography information; generating an estimated peak model based on the posterior probability information, determining a confidence indicator for the estimated peak model, and generating an exception for the at least one peak responsive to the confidence indicator being outside of an exception threshold. Other embodiments are described.

An analysis device produces learning data for training processing of an estimation model More specifically, the analysis device obtains a plurality of reference waveforms for a given type of device. In addition, the analysis device specifies information about a peak for each of the plurality of reference waveforms according to a criterion corresponding to the given type of device. The analysis device assigns the specified information about the peak to each of the plurality of reference waveforms.

A data generation device according to the present invention is a data generation device configured to simulatively generate data used when creating, by machine learning, a discriminator configured to detect a peak observed in a signal waveform, the data generation device including: a parameter frequency information acquisition unit configured to acquire information on frequency of a predetermined shape parameter which characterizes a shape of a signal waveform from a plurality of signal waveforms collected only in a target field of machine learning for creating the discriminator; and a simulated waveform generation unit configured to generate a simulated signal waveform which is able to include overlapping of a plurality of peaks and noise using the information on frequency of the shape parameter, in which the simulated signal waveform is provided as data for training or evaluating machine learning.

A method of performing mass spectrometry includes accessing a series of mass spectra of detected ions derived from components eluting from a chromatography column; obtaining, based on the series of mass spectra, an elution profile including a plurality of detection points representing intensity of at least a set of the detected ions as a function of time; and determining, based on a set of detection points included in the plurality of detection points, a predicted next detection point of the elution profile to be obtained based on a next mass spectrum to be acquired subsequent to acquisition of the series of mass spectra.

A method of optimizing a design parameter for an adsorption column includes developing a first kinetic model and a Linear Driving Force model for a chromatography and ion exchange based adsorption process. Both analytical solutions to the first kinetic model and the Linear Driving Force model are then used to determine an optimal range of the design parameter.

A chromatographic data system processing apparatus includes a liquid feeder, a sample injector, a column that separates samples, a detector, a controller that processes a detected result of the detector, and a data processor that examines and sets operations of the liquid feeder, the column and the detector, and a measurement condition. The data processor generates a three-dimensional graph having three axes related to a pressure, a time, and a number of theoretical plates based on data or variables indicating a relationship between the number of theoretical plates and a flow rate, and data or variables indicating a relationship between the pressure and the flow rate. The chromatographic data system processing apparatus can easily obtain a separation condition for obtaining performance from a three-dimensional graph including a pressure drop, a hold-up time and a number of theoretical plates.

A method for determining a grade of black tea by HPLC detection belongs to the field of tea grade determination. The specific steps are as follows: adding known black tea powder samples of different grades into boiling water of 95-100° C. for extraction, and filtering with a filter membrane with a pore size in a range of 0.20-0.25 μm to obtain black tea sample liquid; measuring contents of ten components by peak area normalization method; standardizing data of the contents of the ten components in a black tea sample solution; carrying out unsupervised principal component analysis; carrying out supervised partial least squares discriminant analysis; carrying out hierarchical clustering analysis on the basis of partial least squares discriminant analysis, and finally establishing a tea grade discrimination model based on HPLC. The method is simple, accurate and efficient, and whose effectiveness is not affected by the variety of black tea.

A non-transitory computer readable medium (CRM) storing computer readable program code for monitoring a state of a chromatography apparatus embodied therein that: receives one or more monitoring conditions that each include a determination condition for parameters related to measurements taken using the chromatography apparatus; and displays, in parallel and using a combination operational expression: a first conditional expression based on at least one of the monitoring conditions that make up a first combined conditional expression, wherein the first combined conditional expression is based on a first combined monitoring condition that combines all of the received monitoring conditions, and a second conditional expression based on at least one of the monitoring conditions associated with the first conditional expression.