A method and system comprising storing a set of user application programs each requiring an application specific subset of data to perform application processes and generate a respective genomic variant characterization for each of a plurality of patients with cancerous cells and receiving cancer treatment. The method including, obtaining clinical records data including cancer related information, generating genomic sequencing data for the patient's cancerous cells and normal cells, shaping at least a subset of the genomic sequencing data to generate system structured data. Storing the system structured data in a first database, selecting the application specific data from the first database, storing the application specific data in a second database for application program interfacing, receiving the respective genomic variant characterization from the user application program, and storing the genomic variant characterization from the user application program in a third database.

A nervous system emulator engine includes working computational models of the vertebrate nervous system to generate lifelike animal behavior in a robot. These models include functions representing several anatomical features of the vertebrate nervous system, such as spinal cord, brainstem, basal ganglia, thalamus and cortex. The emulator engine includes a hierarchy of controllers in which controllers at higher levels accomplish goals by continuously specifying desired goals for lower-level controllers. The lowest levels of the hierarchy reflect spinal cord circuits that control muscle tension and length. Moving up the hierarchy into the brainstem and midbrain/cortex, progressively more abstract perceptual variables are controlled. The nervous system emulator engine may be used to build a robot that generates the majority of animal behavior, including human behavior. The nervous system emulator engine may also be used to build working models of nervous system functions for clinical experimentation.

Methods for identifying biosynthetic gene clusters that include genes for producing compounds that interact with specific target proteins are disclosed. Some methods relate to bioinformatics methods for identifying and/or prioritizing biosynthetic gene clusters. Related systems, components, and tools for the identification and expression of such gene clusters are also disclosed.

Disclosed herein is a system and method for increasing the fidelity of measured genetic data, for making allele calls, and for determining the state of aneuploidy, in one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available. Poorly or incorrectly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related individuals. In accordance with one embodiment, incomplete genetic data from an embryonic cell are reconstructed at a plurality of loci using the more complete genetic data from a larger sample of diploid cells from one or both parents, with or without haploid genetic data from one or both parents. In another embodiment, the chromosome copy number can be determined from the measured genetic data, with or without genetic information from one or both parents.

An example method of treating a subject having a tumor is described herein. The method can include determining a radiosensitivity index of the tumor, deriving a subject-specific variable based on the radiosensitivity index, and obtaining a genomic adjusted radiation dose effect value for the tumor. The radiosensitivity index can be assigned from expression levels of signature genes of a cell of the tumor. Additionally, the genomic adjusted radiation dose effect value can be predictive of tumor recurrence in the subject after treatment. The method can also include determining a radiation dose based on the subject-specific variable and the genomic adjusted radiation dose effect value.

An example method of treating a subject having a tumor is described herein. The method can include determining a radiosensitivity index of the tumor, deriving a subject-specific variable based on the radiosensitivity index, and obtaining a genomic adjusted radiation dose effect value for the tumor. The radiosensitivity index can be assigned from expression levels of signature genes of a cell of the tumor. Additionally, the genomic adjusted radiation dose effect value can be predictive of tumor recurrence in the subject after treatment. The method can also include determining a radiation dose based on the subject-specific variable and the genomic adjusted radiation dose effect value.

This information processing method specifies a disease that a user is likely to suffer from, based on gene analysis data of a user; analyzes behavior history data of the user and operation history data of an apparatus; generates first lifestyle pattern data indicating a lifestyle pattern of the user up to present; executes a simulation for causing a digital twin of the user and a digital twin of the apparatus to operate in cyberspace based on the first lifestyle pattern data, standard lifestyle pattern data, and the operation history data; generates second lifestyle pattern data in which a future lifestyle pattern of the user is predicted, from an execution result of the simulation; and calculates a future illness risk of the user for the specified disease based on the second lifestyle pattern data.

This information processing method specifies a disease that a user is likely to suffer from, based on gene analysis data of a user; analyzes behavior history data of the user and operation history data of an apparatus; generates first lifestyle pattern data indicating a lifestyle pattern of the user up to present; executes a simulation for causing a digital twin of the user and a digital twin of the apparatus to operate in cyberspace based on the first lifestyle pattern data, standard lifestyle pattern data, and the operation history data; generates second lifestyle pattern data in which a future lifestyle pattern of the user is predicted, from an execution result of the simulation; and calculates a future illness risk of the user for the specified disease based on the second lifestyle pattern data.

Disclosed herein are a method for analyzing a genetic interaction to reduce a false positive in gene screening for at least one gene cluster associated with at least one type of cells by deriving the genetic interaction and a synthetic partner with at least one profile selected from the group consisting of a mutation profile, a loss-of-function profile, and an expression profile; and a system using same.

The present invention relates to a method for determining one or more intrinsic properties of a DNA component from a plurality of measurements obtained over a time period from a cell culture, with each cell comprising the DNA component, wherein the DNA component is involved in transcription of one or more target signals, wherein the plurality of measurements comprises measurements relating to the density of the cell culture over the time period and measurements relating to the amount of the one or more target signals in the cell culture over the time period.