145 results about "Genetic data" patented technology

A system and method for determining the genetic data for one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available. Genetic data for the target individual is acquired and amplified using known methods, and poorly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related subjects. In accordance with one embodiment of the invention, incomplete genetic data from an embryonic cell is reconstructed using the more complete genetic data from a larger sample of diploid cells from one or both parents, with or without genetic data from haploid cells from one or both parents, and / or genetic data taken from other related individuals. In accordance with another embodiment of the invention, incomplete genetic data from a fetus is acquired from fetal cells, or cell-free fetal DNA isolated from the mother's blood, and the incomplete genetic data is reconstructed using the more complete genetic data from a larger sample diploid cells from one or both parents, with or without genetic data from haploid cells from one or both parents, and / or genetic data taken from other related individuals. In one embodiment, the genetic data can be reconstructed for the purposes of making phenotypic predictions. In another embodiment, the genetic data can be used to detect for aneuploides and uniparental disomy.

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. Genetic material from the target individual is acquired, amplified and the genetic data is measured using known methods. 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 of the invention, 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 of the invention, the chromosome copy number can be determined from the measured genetic data of a single or small number of cells, with or without genetic information from one or both parents. In another embodiment of the invention, these determinations are made for the purpose of embryo selection in the context of in-vitro fertilization. In another embodiment of the invention, the genetic data can be reconstructed for the purposes of making phenotypic predictions.

A system and method for determining the genetic data for one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available, are disclosed. Genetic data for the target individual is acquired and amplified using known methods, and poorly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related subjects. In accordance with one embodiment of the invention incomplete genetic data is acquired from embryonic cells, fetal cells, or cell-free fetal DNA isolated from the mother's blood, and the incomplete genetic data is reconstructed using the more complete genetic data from a larger sample diploid cells from one or both parents, with or without genetic data from haploid cells from one or both parents, and / or genetic data taken from other related individuals.

A method and system for migrating a computing environment from a source computing platform to a destination computing platform. A script defines at least one software system or application stored on the source computing platform. The script is parsed by a scripting engine to resolve specific user-selectable settings of each source software system or application. Genetic data is generated to represent the resolved settings of the source software systems and / or applications. The genetic data is then selectively applied to corresponding software systems or applications stored on the destination computing platform to automatically provide similar settings thereon.

Systems and methods are described herein for disease knowledge modeling and clinical treatment decision support, and the prioritization of possible treatment options based on tumor or other disease biomarkers. Disease or indication information, including identification of biomolecular entities associated with the indication may be culled through text data mining to create a knowledge model of the indication. In some embodiments, the knowledge model may comprise a network of associations between molecular entities, including such drug targets and biomakers, genes, pathways. The model may be combined with patient-specific variant information and historical treatment records to identify and prioritize treatment decisions and allow for the prediction of disease drivers and provide treatment options tailored to a patient's genetic data.

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.

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.

A method for conducting genetic research on medical data. The method includes the step of accessing a database storing a plurality of medical records associated with a plurality of individuals, each medical record including at least one unique identifier associated with a certain individual and medical data associated with the certain individual. The method also includes the steps of extracting from the database the medical data associated with at least a subset of the plurality of individuals and, for each individual of the subset, obtaining electronically stored genetic data associated with the respective unique identifier. Also, the method includes processing the extracted medical data and obtained genetic data for attempting to identify an association between particular genetic data and a particular medical condition.

Described are computational methods to reconstruct the chromosomes (and genomes) of ancestors given genetic data, IBD information, and full or partial pedigree information of some number of their descendants.

Described herein is a framework for predicting development of a cardiovascular condition of interest in a patient. The framework involves determining, based on prior domain knowledge relating to the cardiovascular condition of interest, a risk score as a function of patient data. The patient data may include both genetic data and non-genetic data. In one implementation, the risk score is used to categorize the patient into at least one of multiple risk categories, the multiple risk categories being associated with different strategies to prevent the onset of the cardiovascular condition. The results generated by the framework may be presented to a physician to facilitate interpretation, risk assessment and / or clinical decision support.

A method, software, database and system for attribute partner identification and social network based attribute analysis are presented in which attribute profiles associated with individuals can be compared and potential partners identified. Connections can be formed within social networks based on analysis of genetic and non-genetic data. Degrees of attribute separation (genetic and non-genetic) can be utilized to analyze relationships and to identify individual who might benefit from being connected.

The present invention is directed to methods and systems for improving the efficiency of livestock production using genetic information obtained from the animal. The methods of the invention comprise obtaining a genetic sample from an animal or embryo, determining the genotype of the animal or embryo with respect to specific quality traits, grouping animals with like genotypes, and optionally, further sub-grouping animals based on like phenotypes. Based on the genotype, an animal is treated in a particular way. For example, uniform feeding regimens are designed for a particular group so as to maximize feed efficiencies and accurately predict slaughter times among like animals possessing a desired quality trait. Such methods include obtaining and maintaining the genetic data obtained from each animal, and optionally other data relating to the animal's health, condition or parentage, or to its herd, and providing this data to others through systems that are web-based, contained in a database, or attached to the animal itself such as by an implanted microchip.

The principles of the present invention provide methods and systems for processing personal biological data for real time or near real time application. An exemplary system includes a received reference genome and a received personal genome. The genomes are accessed over a network by one or more servers. Input from one or more sensors associated with an individual or remote from the individual is used in conjunction with the individual's genomic data or the results of the comparison of the individual's genetic data and the reference genome(s) to provide real-time or near real-time suggestions, recommendations, warnings and the like in view of the sensor data and genomic data. An exemplary method includes receiving the personal genome and optionally selecting a suitable reference genome. The system compares the personal genome to the reference genome, of parts thereof, for one or more selected genotype(s) and / or phenotype(s) corresponding to a condition of concern in order to determine the differences between the reference genome and the personal genome. A sensor corresponding either directly or indirectly to the selected condition of concern is selected and optimum values for the sensor are calculated. The sensor is placed in proximity with the individual and the output is monitored. Alerts and reporting are presented in response to the sensor output. The present invention concerns systems and methods for analysis of biological data and integration of such data into everyday life.

The invention relates to a gene classification method and system based on clustering and random forest algorithms and belongs to the technical field of biological information. The method comprises a step of acquiring gene sample data, clustering the acquired gene sample data by using the clustering algorithm to obtain a cluster center, and supplementing a training sample set with an obtained cluster center set, a step of adjusting the number of fixed decision tree random description attributes in a traditional random forest algorithm to a random value, wherein on one hand, strong decision trees in a decision tree set are kept, on the other hand, the number of average random description attributes of the decision tree set is reduced, thus the correlation between the decision trees is further reduced, and a step of predicting genetic data to be classified by using each decision tree in a random forest model. According to the method and the system, the cluster center obtained through theclustering algorithm is taken as artificial data to expand the training set of the random forest model, thus the random forest model is fully trained, the obtained classification model has high precision, and the accuracy of the classification of genetic data is improved.