[Object] It is desirable to realize a more efficient coordination between the genetic analysis company and the medical institution. [Solution] Provided is an information processing device including: a data acquisition unit configured to acquire predetermined information; a determination unit configured to determine whether or not personal information of a subject has been set in the predetermined information; and an identification information provision unit configured to provide a medical institution terminal with user identification information required when the subject uses a service, in a case where it is determined that the personal information of the subject has not been set in the predetermined information.

Embodiments of a method and system for microbial pharmacogenomics can include: a sample handling system operable to collect containers including biological samples from a set of users, the handling system including a sequencing system operable to determine microorganism sequences from the biological samples; a microbiome characterization system operable to: determine microbiome pharmacogenomics data based on the microorganism sequences, collect supplementary data associated with the antibiotics-associated condition for the set of users, and transform the supplementary data and features extracted from the microbiome pharmacogenomics data into a characterization model associated with the antibiotics-associated condition; and a treatment system operable to promote a treatment to the user for the antibiotics-associated condition based on characterizing user biological material with the characterization model in relation to the antibiotics-associated condition.

A method for transferring a dataset-specific nature of a first dataset with sequencing results for a first plurality of specimen to a second dataset with sequencing results for a second plurality of specimen includes receiving a first set of adaptation factors of the first dataset that include two or more eigenvectors, where the sequencing cannot be reconstructed from the first set of adaptation factors without access to the first dataset. The method also includes generating a second set of adaptation factors of the second dataset that include two or more eigenvectors of the second dataset. The method also includes generating an adapted second dataset by adapting the dataset-specific nature of the second dataset to the dataset-specific nature of the second dataset based at least in part on the first and second sets of adaptation factors, and providing the adapted second dataset to the first entity.

A method for transferring a dataset-specific nature of a first dataset with sequencing results for a first plurality of specimen to a second dataset with sequencing results for a second plurality of specimen includes receiving a first set of adaptation factors of the first dataset that include two or more eigenvectors, where the sequencing cannot be reconstructed from the first set of adaptation factors without access to the first dataset. The method also includes generating a second set of adaptation factors of the second dataset that include two or more eigenvectors of the second dataset. The method also includes generating an adapted second dataset by adapting the dataset-specific nature of the second dataset to the dataset-specific nature of the second dataset based at least in part on the first and second sets of adaptation factors, and providing the adapted second dataset to the first entity.

Systems and methods are provided for improved integration between database systems. Data from multiple disparate computing systems is transmitted via bi-directional communication interfaces. The data is stored in its original form from respective data sources and transformed in stream and/or batch processes into one or more predefined formats. Individual transformations are stored and/or recorded. The transformed and/or integrated data is provided to one or more computing devices via the communication interfaces.

Systems and methods are provided for improved integration between database systems. Data from multiple disparate computing systems is transmitted via bi-directional communication interfaces. The data is stored in its original form from respective data sources and transformed in stream and/or batch processes into one or more predefined formats. Individual transformations are stored and/or recorded. The transformed and/or integrated data is provided to one or more computing devices via the communication interfaces.

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 computer implemented method for predicting an agronomical value and a breeding value of a plant belonging to a population, the method includes the steps of: obtaining at least some genotypic data from a subset of lines from the population, obtaining at least some phenotypic data from a subset of lines from the population, providing a statistical model receiving in input the genotypic data and phenotypic data, using the statistical model to output at least an agronomical value estimated for the plant. More particularly, the statistical model is a mixed model combining fixed effects and random effects.

A computer implemented method for predicting an agronomical value and a breeding value of a plant belonging to a population, the method includes the steps of: obtaining at least some genotypic data from a subset of lines from the population, obtaining at least some phenotypic data from a subset of lines from the population, providing a statistical model receiving in input the genotypic data and phenotypic data, using the statistical model to output at least an agronomical value estimated for the plant. More particularly, the statistical model is a mixed model combining fixed effects and random effects.

A data generation method includes: with regard to a target in which a plurality of sets of reference source data and reference target data are connectable by using edges, extracting information that corresponds to a complete bipartite graph from the connected target; and when there are a plurality of sets of reference source data and a plurality of sets of reference target data that are the extracted information and that constitute the complete bipartite graph, generating a virtual node between the reference source data and the reference target data.