A bioinformatics method for determining a risk score that indicates a risk that a subject, in particular a human, will experience a negative clinical event within a certain period of time. The risk score is based on a unique combination of activities of two or more cellular signaling pathways in a subject, wherein the selected cellular signaling pathways are the TGF-β pathway and one or more of a PI3K pathway, a Wnt pathway, an ER pathway, and an HH pathway. The invention includes an apparatus with a digital processor configured to perform such a method, a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and a computer program comprising program code means for causing a digital processing device to perform such a method. The bioinformatics invention allows for more accurate prognosis of specific negative clinical events in a patient with, for example, a tumor or cancer, such as disease progression, recurrence, development of metastasis, or even death.

A system and method for identification of key driver responsible for bringing changes in a microbial population is provided. The method involves construction of microbial association networks with each microbial taxa as nodes and their associations as edges and subsequent identification of crucial ‘driver’ nodes involved in the studied disease progression. While comparing a particular node between two networks, this method takes individual nodes and their associations into account as well as the identity of their interacting partners. A taxon in the diseased state with an altered set of associations while still being increasingly important for the whole network necessarily holds a key significance in microbial interplay. Using this rationale, this methodology computes a score to quantify this change for each node and calculates its statistical significance. Subsequently, ‘driver’ nodes are identified using the score coupled with other network parameters and a critical score for the ‘driver’ nodes is calculated to quantify its importance.

A system and method for identification of key driver responsible for bringing changes in a microbial population is provided. The method involves construction of microbial association networks with each microbial taxa as nodes and their associations as edges and subsequent identification of crucial ‘driver’ nodes involved in the studied disease progression. While comparing a particular node between two networks, this method takes individual nodes and their associations into account as well as the identity of their interacting partners. A taxon in the diseased state with an altered set of associations while still being increasingly important for the whole network necessarily holds a key significance in microbial interplay. Using this rationale, this methodology computes a score to quantify this change for each node and calculates its statistical significance. Subsequently, ‘driver’ nodes are identified using the score coupled with other network parameters and a critical score for the ‘driver’ nodes is calculated to quantify its importance.

The invention belongs to the technical field of the molecular force field and particularly relates to a computing task management and analysis system for molecular force field parameter building and an operation method thereof. The system comprises a computing result analysis module and a computing task management module, the computing result analysis module is connected with the computing task management module, and the computing task management module is connected with a force field building computing server through a cloud computing interface. The operation method comprises: (1) selecting a molecular force field building computing templates; (2) selecting a computing task submitting platform and submitting computing tasks; (3) retrieving computing results; and (4) analyzing the computing results. According to the invention, since force field building system users mainly including researchers do not have powerful open interface development capacity commonly, a convenient cloud computing calling interface is provided, and the force field building speed is improved; the system provides full-view and visual effects; an interactive analysis mode is provided for the force field building computing results, which facilitates quick location of a computing exception; and automatic task processing and analysis are supported.

The invention belongs to the technical field of the molecular force field and particularly relates to a computing task management and analysis system for molecular force field parameter building and an operation method thereof. The system comprises a computing result analysis module and a computing task management module, the computing result analysis module is connected with the computing task management module, and the computing task management module is connected with a force field building computing server through a cloud computing interface. The operation method comprises: (1) selecting a molecular force field building computing templates; (2) selecting a computing task submitting platform and submitting computing tasks; (3) retrieving computing results; and (4) analyzing the computing results. According to the invention, since force field building system users mainly including researchers do not have powerful open interface development capacity commonly, a convenient cloud computing calling interface is provided, and the force field building speed is improved; the system provides full-view and visual effects; an interactive analysis mode is provided for the force field building computing results, which facilitates quick location of a computing exception; and automatic task processing and analysis are supported.

A personalized health formula system which combines genetic and metabolic data to generate personalized intervention plan, termed Genetic and Metabolic Data Associated Intervention (GMDAI), as well as a computer readable medium and device containing the same is disclosed. The GMDAI personalized health formula system includes a pathway decision module and a supplement intervention module. The pathway decision module can make a decision of increasing or decreasing one or more of the markers by weighing detected levels of these markers, and the supplement intervention module can recommend a personalized supplementation formula including the type and dosage of supplement.

A personalized health formula system which combines genetic and metabolic data to generate personalized intervention plan, termed Genetic and Metabolic Data Associated Intervention (GMDAI), as well as a computer readable medium and device containing the same is disclosed. The GMDAI personalized health formula system includes a pathway decision module and a supplement intervention module. The pathway decision module can make a decision of increasing or decreasing one or more of the markers by weighing detected levels of these markers, and the supplement intervention module can recommend a personalized supplementation formula including the type and dosage of supplement.

One variation of a method for detecting pathogens includes: accessing a timeseries of pathogen data for a pathogen, in a set of pathogens, derived from a series of pathogen samples collected in an environment during a time period; characterizing a pathogen profile, representative of changes in pathogen level of the first pathogen in the environment during the time period, based on the timeseries of pathogen data; accessing a baseline pathogen profile representative of changes in pathogen levels of the set of pathogens in the environment during an initial time period preceding the time period; characterizing a difference between the pathogen profile and the baseline pathogen profile; and, in response to the difference exceeding a threshold difference, selecting a mitigation action configured to reduce pathogen levels of the first pathogen and transmitting a prompt to execute the mitigation action to a user associated with the indoor environment.

A method for generating an immune score, the method comprising the steps of: (i) determining a qualitative and/or quantitative assessment of tumor infiltrating lymphocytes in a sample; (ii) determining a qualitative and/or quantitative assessment of T-cell receptor signaling in the sample; (iii) determining a qualitative and/or quantitative assessment of mutation burden in the sample; (iv) generating, using a predictive algorithm, an immune score based on the determined qualitative and/or quantitative assessment of tumor infiltrating lymphocytes, the determined qualitative and/or quantitative assessment of T-cell receptor signaling, and the determined qualitative and/or quantitative assessment of mutation burden.

A method for generating an immune score, the method comprising the steps of: (i) determining a qualitative and/or quantitative assessment of tumor infiltrating lymphocytes in a sample; (ii) determining a qualitative and/or quantitative assessment of T-cell receptor signaling in the sample; (iii) determining a qualitative and/or quantitative assessment of mutation burden in the sample; (iv) generating, using a predictive algorithm, an immune score based on the determined qualitative and/or quantitative assessment of tumor infiltrating lymphocytes, the determined qualitative and/or quantitative assessment of T-cell receptor signaling, and the determined qualitative and/or quantitative assessment of mutation burden.