Patent classifications
G16B50/00
Cell-free DNA methylation patterns for disease and condition analysis
Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.
Systems and methods for generating personalized skincare formulations based on biomarker analysis
Systems and methods are provided for improving skincare product formulations to address predicted skin trends. A biomarker analysis system is used to determine concentrations of various protein biomarkers of a user. A skin diagnosis computing device uses the protein biomarker concentrations to determine one or more skin trends, and determines one or more skincare product ingredients to address the skin trends. A skincare product is compounded that includes the one or more skincare product ingredients.
Systems and methods for generating personalized skincare formulations based on biomarker analysis
Systems and methods are provided for improving skincare product formulations to address predicted skin trends. A biomarker analysis system is used to determine concentrations of various protein biomarkers of a user. A skin diagnosis computing device uses the protein biomarker concentrations to determine one or more skin trends, and determines one or more skincare product ingredients to address the skin trends. A skincare product is compounded that includes the one or more skincare product ingredients.
METHODS AND SYSTEMS FOR DETECTING SEQUENCE VARIANTS
The invention provides methods for identifying rare variants near a structural variation in a genetic sequence, for example, in a nucleic acid sample taken from a subject. The invention additionally includes methods for aligning reads (e.g., nucleic acid reads) to a reference sequence construct accounting for the structural variation, methods for building a reference sequence construct accounting for the structural variation or the structural variation and the rare variant, and systems that use the alignment methods to identify rare variants. The method is scalable, and can be used to align millions of reads to a construct thousands of bases long, or longer.
METHODS AND SYSTEMS FOR DETECTING SEQUENCE VARIANTS
The invention provides methods for identifying rare variants near a structural variation in a genetic sequence, for example, in a nucleic acid sample taken from a subject. The invention additionally includes methods for aligning reads (e.g., nucleic acid reads) to a reference sequence construct accounting for the structural variation, methods for building a reference sequence construct accounting for the structural variation or the structural variation and the rare variant, and systems that use the alignment methods to identify rare variants. The method is scalable, and can be used to align millions of reads to a construct thousands of bases long, or longer.
Neurological data processing
The present invention is in the technical field of bioinformatics, and the implementation of bioinformatics. Advances in technology have led to a large increase in the rate at which data, in particular in the medical domain, can be generated (from patient sources, clinical trials, and research campaigns). The researcher is thus confronted with a large amount of information, and it is difficult to discover connections in the data, and thus to improve medical knowledge, even in spite of the amount of data available. The present application proposes to process and to structure medical data using a computer-implemented semantic network, enabling undiscovered connections between experiments and data sources to be made, and to continually add new data to the semantic network. In summary, it is proposed to provide a computer-implemented method and associated system which are able to automatically provide neurological knowledge model data by annotating neural connectivity data with further data sources.
Neurological data processing
The present invention is in the technical field of bioinformatics, and the implementation of bioinformatics. Advances in technology have led to a large increase in the rate at which data, in particular in the medical domain, can be generated (from patient sources, clinical trials, and research campaigns). The researcher is thus confronted with a large amount of information, and it is difficult to discover connections in the data, and thus to improve medical knowledge, even in spite of the amount of data available. The present application proposes to process and to structure medical data using a computer-implemented semantic network, enabling undiscovered connections between experiments and data sources to be made, and to continually add new data to the semantic network. In summary, it is proposed to provide a computer-implemented method and associated system which are able to automatically provide neurological knowledge model data by annotating neural connectivity data with further data sources.
Apparatus and method for determining validity of bio-information estimation model
An apparatus for determining a validity of a bio-information estimation model includes a data acquirer interface configured to acquire an in vivo spectrum of an object, and acquire bio-information and a concentration of a main component which are estimated based on the in vivo spectrum and a bio-information estimation model; and a processor configured to acquire a residual spectrum of the acquired in vivo spectrum based on the acquired in vivo spectrum, the acquired bio-information, and the acquired concentration of the main component, determine a similarity between the acquired residual spectrum and a reference residual spectrum, and determine the validity of the bio-information estimation model based on the determined similarity.
Apparatus and method for determining validity of bio-information estimation model
An apparatus for determining a validity of a bio-information estimation model includes a data acquirer interface configured to acquire an in vivo spectrum of an object, and acquire bio-information and a concentration of a main component which are estimated based on the in vivo spectrum and a bio-information estimation model; and a processor configured to acquire a residual spectrum of the acquired in vivo spectrum based on the acquired in vivo spectrum, the acquired bio-information, and the acquired concentration of the main component, determine a similarity between the acquired residual spectrum and a reference residual spectrum, and determine the validity of the bio-information estimation model based on the determined similarity.
SINGLE MOLECULE SEQUENCING PEPTIDES BOUND TO THE MAJOR HISTOCOMPATIBILITY COMPLEX
The present disclosure provides methods of identifying and quantifying the peptides displayed by the major histocompatibility complex (MHC). Such methods may comprise the ability to determine the type, identity, and quantity of each peptide displayed by the MHC. In some embodiments, these methods may be used to develop an anti-cancer therapy or type the HLA of a patient. Also provided herein are compositions comprising peptides from the MHC which have been prepared for sequencing.