In one implementation, a computer-implemented method includes accessing patient-derived blood data; identifying biomarker pair interactions based on signal processing of the patient-derived blood data; generating a data model that characterizes one or more aspects of human immune system interactions based on reverse engineering of the human immune system interactions using the identified biomarker pair interactions; evaluating suitability of the data model, wherein the evaluating includes: statistically testing the data model in characterizing correlations between biomarker pairs; decomposing the data model to determine (i) model order accuracy, (ii) whether biomarker nodes act in together or opposite each other, and (iii) normalized data with dynamic effects of homeostasis removed; and quantifying degrees to which the data model accurately correlates patient treatments to patient outcomes; and providing the data model for use in treatment-based decision making based on the evaluating.

In one implementation, a computer-implemented method includes accessing patient-derived blood data; identifying biomarker pair interactions based on signal processing of the patient-derived blood data; generating a data model that characterizes one or more aspects of human immune system interactions based on reverse engineering of the human immune system interactions using the identified biomarker pair interactions; evaluating suitability of the data model, wherein the evaluating includes: statistically testing the data model in characterizing correlations between biomarker pairs; decomposing the data model to determine (i) model order accuracy, (ii) whether biomarker nodes act in together or opposite each other, and (iii) normalized data with dynamic effects of homeostasis removed; and quantifying degrees to which the data model accurately correlates patient treatments to patient outcomes; and providing the data model for use in treatment-based decision making based on the evaluating.

The present invention provides for a simultaneous graphical representation, a risk of bleeding and a risk of thrombosis providing a visualized bridge therapy process. Furthermore, the present invention provides for a computer-based prediction of the haemostatic situation of the examined blood circulation by using a combination of a biochemical model and a pharmacokinetic model for calculation or another mathematical representation of the blood circulation.

Methods and systems for knowledge pattern search and analysis for selecting microorganisms based on desired metabolic properties or biological behaviors are disclosed in various embodiments of the invention. In one embodiment of the invention, a computer-implemented method for selecting a purpose-specific microorganism first compiles microorganisms' profiles by linking each microorganism's methanogenic, hydrogenic, electrogenic, another metabolic property, and/or another biological behavior to genetic and chemical fingerprints of metabolic and energy-generating biological pathways. Then, based on the compiled profiles of the microorganisms, the computer-implemented method groups the microorganisms into pathway characteristics using machine-learning and pattern recognition performed on a computer system, and subsequently generates a prediction called “discovered characteristics” for a desired metabolic property or a desired biological behavior of at least one microorganism. Furthermore, a profile match score may be calculated to indicate usefulness of one or more microorganisms for renewable energy generation from biological waste materials or wastewater.

A method for making a modified release composition, comprising: selecting a desired active agent and polymer matrix for formulating into a modified release composition; assessing degradation effect on release of the active agent from the composition including plotting polymer molecular weight (M.sub.wr) at onset of active agent release vs. active agent molecular weight (M.sub.wA); predicting performance of multiple potential formulations for the composition based on the degradation assessment and average polymer matrix initial molecular weight (M.sub.wo) to define a library of building blocks; determining the optimal ratio of the building blocks to satisfy a specified release profile; and making a modified release composition based on the optimal ratio determination.

A method includes obtaining data measurements associated with plants in at least one growing area. The plants have a common genotype and are grown under different growing or environmental conditions in the at least one growing area. The data measurements are associated with one or more characteristics of the plants and multiple characteristics of the growing or environmental conditions. The method also includes processing at least some of the data measurements to identify one or more of the growing or environmental conditions associated with at least one desired characteristic being expressed in the plants being grown. The method further includes outputting an identification of the one or more growing or environmental conditions identified as achieving a specific genotype or phenotype trait for the plants. The specific genotype or phenotype trait is associated with the at least one desired characteristic.

A method includes obtaining data measurements associated with plants in at least one growing area. The plants have a common genotype and are grown under different growing or environmental conditions in the at least one growing area. The data measurements are associated with one or more characteristics of the plants and multiple characteristics of the growing or environmental conditions. The method also includes processing at least some of the data measurements to identify one or more of the growing or environmental conditions associated with at least one desired characteristic being expressed in the plants being grown. The method further includes outputting an identification of the one or more growing or environmental conditions identified as achieving a specific genotype or phenotype trait for the plants. The specific genotype or phenotype trait is associated with the at least one desired characteristic.

Improved human health monitoring is provided in the context of sensor measurements of typical vital signs and other biological parameters, by a system and method using an empirical model of the parameters and disposed to estimate values of the parameters in response to actual measurements. Residuals resulting from the difference between the estimates and actual measurements are analyzed for robust indications of incipient health issues. Residual analysis is both more robust and more sensitive than conventional univariate range checking on vital signs.

The present disclosure relates to general and scalable techniques for modeling in silico the kinetics of systems of connected biochemical reactions. Particularly, aspects of the present disclosure are directed to deconstructing a reaction into a plurality of component steps, translating each component step into a set of rate equations to obtain a standard mathematical construct or model representing each component step, numerically integrating across the standard mathematical constructs or models using a system of ordinary differential equations to determine a contribution of each component step to a rate of change of molecules within reaction, and deriving a in silico behavior of a system utilizing the reaction based on the contribution of each component step to the rate of change of the molecules within the reaction. The standard mathematical constructs or models may be parameterized based on an energy profile for the reaction inferred from machine-learning approaches.

The present disclosure relates to general and scalable techniques for modeling in silico the kinetics of systems of connected biochemical reactions. Particularly, aspects of the present disclosure are directed to deconstructing a reaction into a plurality of component steps, translating each component step into a set of rate equations to obtain a standard mathematical construct or model representing each component step, numerically integrating across the standard mathematical constructs or models using a system of ordinary differential equations to determine a contribution of each component step to a rate of change of molecules within reaction, and deriving a in silico behavior of a system utilizing the reaction based on the contribution of each component step to the rate of change of the molecules within the reaction. The standard mathematical constructs or models may be parameterized based on an energy profile for the reaction inferred from machine-learning approaches.