Disclosed herein are methods for making a transcriptome-wide expression profile of a biological sample and identifying biomarkers that can be used to diagnose, monitor the onset, monitor the progression, and assess the recovery of a disease in a subject. The biomarkers can also be used to establish and evaluate treatment regimens.

Disclosed herein are methods for making a transcriptome-wide expression profile of a biological sample and identifying biomarkers that can be used to diagnose, monitor the onset, monitor the progression, and assess the recovery of a disease in a subject. The biomarkers can also be used to establish and evaluate treatment regimens.

A computer-executable application receives genetic test results for a genetic test a patient has undergone, an identifier for the genetic test, and an identifier for the genetic laboratory that performed the genetic test. The application identifies a format type of the genetic test results. When the format type is unstructured, the application performs an optical character recognition process to the genetic test results such that the format type of the genetic test results is semi-structured. When the format type is semi-structured, the application identifies a set of lexing and parsing rules assigned to the genetic test. The application generates processed genetic test results by applying the set of lexing and parsing rules to the genetic test results and stores the processed genetic test results in a data store. When the format type is structured, the application stores the genetic test results as the processed genetic test results in the data store.

A computer-executable application receives genetic test results for a genetic test a patient has undergone, an identifier for the genetic test, and an identifier for the genetic laboratory that performed the genetic test. The application identifies a format type of the genetic test results. When the format type is unstructured, the application performs an optical character recognition process to the genetic test results such that the format type of the genetic test results is semi-structured. When the format type is semi-structured, the application identifies a set of lexing and parsing rules assigned to the genetic test. The application generates processed genetic test results by applying the set of lexing and parsing rules to the genetic test results and stores the processed genetic test results in a data store. When the format type is structured, the application stores the genetic test results as the processed genetic test results in the data store.

The present disclosure provides a novel integrated entropy-based method that combines genome-wide profiling and network analyses for diagnostic and prognostic applications. The present disclosure further provides the integration of multiomics datasets, network analyses and machine learning that enable predictions on diagnosing infectious diseases and predicting the probability that they will escape treatment/the host immune system and/or become antibiotic resistant. The present disclosure provides a primary gateway towards the development of highly accurate infectious disease prognostics.

The present disclosure provides a novel integrated entropy-based method that combines genome-wide profiling and network analyses for diagnostic and prognostic applications. The present disclosure further provides the integration of multiomics datasets, network analyses and machine learning that enable predictions on diagnosing infectious diseases and predicting the probability that they will escape treatment/the host immune system and/or become antibiotic resistant. The present disclosure provides a primary gateway towards the development of highly accurate infectious disease prognostics.

Provided herein are methods for accurately determining the alleles present at a locus that is broadly applicable to any locus, including highly polymorphic loci such as HLA loci, BGA loci and HV loci. Embodiments of the disclosed methods are useful in a wide range of applications, including, for example, organ transplantation, personalized medicine, diagnostics, forensics and anthropology.

Provided herein are methods for accurately determining the alleles present at a locus that is broadly applicable to any locus, including highly polymorphic loci such as HLA loci, BGA loci and HV loci. Embodiments of the disclosed methods are useful in a wide range of applications, including, for example, organ transplantation, personalized medicine, diagnostics, forensics and anthropology.

Contemplated systems and methods allow for prediction of chemotherapy outcome for patients diagnosed with high-grade bladder cancer. In particularly preferred aspects, the prediction is performed using a model based on machine learning wherein the model has a minimum predetermined accuracy gain and wherein a thusly identified model provides the identity and weight factors for omics data used in the outcome prediction.

This invention provides methods for identifying genes associated with cognitive impairment and for identifying compounds useful in the treatment of cognitive impairment. The methods can in particular be used to identify genes associated with, and compounds useful in treating, cognitive impairment in aging.