Abstract: A computing system is provided in which sparse vectors is obtained. Each vector represents a single entity, and has at least ten thousand elements each of which represents an entity feature. Less than ten percent of the elements in each vector is present in the input data. The vectors are applied to a plurality of denoising autoencoders. Each respective autoencoder, other than the final autoencoder, feeds intermediate values as a function of (i) a weight coefficient matrix and bias vector associated with the respective autoencoder and (ii) input values received by the autoencoder, into another autoencoder. The final autoencoder outputs a dense vector, consisting of less than 1000 elements, for each sparse vector thereby forming a plurality of dense vectors. A post processor engine is trained on the plurality of dense vectors causing the engine to predict a future change in a value for a feature for a test entity.

Abstract: The present invention provides methods embodied in a system that can be applied to genetic information comprising an individual genome to assess the regulatory impact of specific genetic variants and their possible impact on biological function or disease pathology.

Abstract: Measuring of the binding of a transcription factor (using, for example, chromatin immunoprecipitation) according to the present invention is provides an improved marker for a disease. These markers can be used in diagnostics for diseases where a transcription factor binding event plays a role. Additionally, they can be used to adjust disease risk profiles for healthy individuals as with typical genetic variants.

Abstract: Measuring of the binding of a transcription factor (using, for example, chromatin immunoprecipitation) according to the present invention is provides an improved marker for a disease. These markers can be used in diagnostics for diseases where a transcription factor binding event plays a role. Additionally, they can be used to adjust disease risk profiles for healthy individuals as with typical genetic variants.

Abstract: Methods and systems are provided for the computation and display of an individual's personalized health risk based on the genome sequence of the individual, known etiological interactions between diseases for which the individual is determined to have genetic risk factors, and environmental etiological factors associated with the same diseases that represent potentially modifiable disease risk modifiers.

Abstract: The present invention provides methods embodied in a system that can be applied to genetic information comprising an individual genome to assess the regulatory impact of specific genetic variants and their possible impact on biological function or disease pathology.

Abstract: Measuring of the binding of a transcription factor (using, for example, chromatin immunoprecipitation) according to the present invention is provides an improved marker for a disease. These markers can be used in diagnostics for diseases where a transcription factor binding event plays a role. Additionally, they can be used to adjust disease risk profiles for healthy individuals as with typical genetic variants.

Abstract: Embodiments of the present invention provide methods and systems that perform comprehensive assessment of genetic variation presenting in a personal genome and provide quantitative diagnosis of the impact of each variant on physiological function and patient health.

Abstract: Methods and systems are provided for the computation and display of an individual's personalized health risk based on the genome sequence of the individual, known etiological interactions between diseases for which the individual is determined to have genetic risk factors, and environmental etiological factors associated with the same diseases that represent potentially modifiable disease risk modifiers.