Abstract: A unified platform may comprise a combination of independent frameworks that have been integrated and configured to collaboratively operate seamlessly. In some aspects, the unified platform may comprise one or more of an authentication and authorization framework, a dynamic user interface framework, a workflow state management framework, a notification and active data loss and prevention (DLP) engine framework, and an orchestration engine framework. Each of the frameworks included in the unified platform may comprise one or more of the plurality of computing devices executing computer-readable program instructions.

Abstract: A unified platform may comprise a combination of independent frameworks that have been integrated and configured to collaboratively operate seamlessly. In some aspects, the unified platform may comprise one or more of an authentication and authorization framework, a dynamic user interface framework, a workflow state management framework, a notification and active data loss and prevention (DLP) engine framework, and an orchestration engine framework. Each of the frameworks included in the unified platform may comprise one or more of the plurality of computing devices executing computer-readable program instructions.

Abstract: Disclosed herein are compositions, systems, and methods for identifying neurological diseases from biological sample analysis. A biological sample from a subject may be contacted to a particle to form a biomolecule corona, which may contain a subset of biomolecules from the biological sample and which can have utility for diagnosing a neurological disease state. Further disclosed herein are machine learning algorithms and trained classifiers for distinguishing neurological disease states based on biological data.

Abstract: A number of methods and computer systems related to mass spectrometric data analysis are disclosed. Adoption of the disclosure herein facilitates automated, high throughput, rapid analysis of complex datasets such as datasets generated through mass spectrometric analysis, so as to reduce or eliminate the need for oversight in the analysis process while rapidly yielding accurate results. In some cases, identification of a health condition indicator is carried out based on information relating a predetermined association between an input parameter and a health condition indicator.

Abstract: Systems, methods, filters, and devices are disclosed for quality control monitoring for samples collected and stored on filters. Sample collection devices and filters have markers that act as quality control indicators for one or more procedures involving a sample such as collection, storage, transport, and elution. Practice of the disclosure herein allows for sample evaluation to enhance downstream applications such as ongoing monitoring of a patients health status through the accurate, repeatable measurement of markers in a sample. Reference biomarkers can be used to enhance assessment of health status. In some cases, the present disclosure enables the detection of a disease signal and assessment of disease status through the measurement and analysis of biomarkers in a sample.

Abstract: Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.

Abstract: A number of methods and computer systems related to mass spectrometric data analysis are disclosed. Adoption of the disclosure herein facilitates automated, high throughput, rapid analysis of complex datasets such as datasets generated through mass spectrometric analysis, so as to reduce or eliminate the need for oversight in the analysis process while rapidly yielding accurate results.

Abstract: Databases methods and reagents are disclosed for the generation of large amounts of biomarker data from readily obtained sample such as dried plasma spots, and for uses of such databases in the development of patient categorization or detection of changes in a patient's health status over time.

Abstract: Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

Abstract: Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.

Abstract: Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.

Abstract: Disclosed herein are panels related to the diagnosis or recognition of colon and colorectal cancer in a subject. The disclosed panels and related methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.

Abstract: The disclosed methods are used to predict or assess colon tumor status in a patient. They can be used to determine nature of tumor, recurrence, or patient response to treatments. Some embodiments of the methods include generating a report for clinical management. The methodology provided herein is intended to detect technical variations and to allow for data normalization and enhance signal detection and build predictive proteins profiles of disease status and response.