MICROBIOME BASED SYSTEMS, APPARATUS AND METHODS FOR MONITORING AND CONTROLLING INDUSTRIAL PROCESSES AND SYSTEMS
There are provided methods, systems and processes for the utilization of microbial and related genetic information for use in industrial settings, such as the exploration, determination, and recovery of natural resources, minerals, and energy sources, the monitoring and analysis of processes, activities, and materials transmission.
1 . (canceled)
2 . A system comprising:
a computer having one or more computer processors, the computer configured to perform operations comprising:
generating, using the one or more computer processors, microbiome information from genetic material extracted from one or more samples sourced from a microbiome associated with a waste management industrial operation;
identifying, using the one or more computer processors, a presence of one or more strains of a virus in the microbiome based on an analysis of the microbiome information, the analysis including conducting one or more censuses of microorganisms present in the one or more samples and determining, from a first construct of n-dimensional space information, one or more interrelationships between the microorganisms, the first construct having at least four dimensions;
computationally distilling, using the one or more computer processors, the first construct into a second construct of n-dimensional space information, the second construct having two or three dimensions; and
communicating, using the one or more computer processors, the second construct for display in a human machine interface.
3 . The system of claim 2 , wherein the computational distilling includes transforming the first construct of the n-dimensional space information into the second construct of the n-dimensional space information using one or more mathematical transformation functions, the one or more mathematical functions based on factors or features that are of significance to the microbiome associated with the waste management industrial information, the factors or features being computationally determined.
4 . The system of claim 3 , wherein the computational determining of the factors or features includes using machine learning or multivariate statistical techniques.
5 . The system of claim 2 the operations further comprising returning the second construct of n-dimensional space information to the first construct of n-dimensional space information using the one or more mathematical transformation functions.
6 . The system of claim 2 , wherein the analysis further includes building a phylogenetic tree using aligned sequences matched to the one or more samples.
7 . The system of claim 2 , wherein each of the one or more strains has a different molecular function.
8 . The system of claim 2 , wherein the one or more censuses are obtained over one or more time points.
9 . The system of claim 8 , wherein the second construct includes a plot that visualizes patterns corresponding to the one or more samples over a time period corresponding to the one or more time points.
10 . The system of claim 2 , wherein the microorganisms include components other than bacteria and archaea.
11 . The system of claim 2 , wherein the generating of the microbiome information includes deriving the microbiome information from one or more fragments of any genetic material detected in the one or more samples.
12 . A method comprising:
generating, using one or more computer processors, microbiome information from genetic material extracted from one or more samples sourced from a microbiome associated with a waste management industrial operation;
identifying, using the one or more computer processors, a presence of one or more strains of a virus in the microbiome based on an analysis of the microbiome information, the analysis including conducting one or more censuses of microorganisms present in the one or more samples and determining, from a first construct of n-dimensional space information, one or more interrelationships between the microorganisms the first construct of n-dimensional having at least four dimensions;
computationally distilling, using the one or more computer processors, the first construct into a second construct of n-dimensional space information, the second construct having two or three dimensions; and
communicating, using the one or more computer processors, the second construct for display in a human machine interface.
13 . The method of claim 12 , wherein the computational distilling includes transforming the first construct of n-dimensional space information into the second construct of n-dimensional space information using one or more mathematical transformation functions, the one or more mathematical functions based on factors or features that are of significance to the microbiome associated with the waste management industrial information, the factors or features being computationally determined.
14 . The method of claim 13 , wherein the computational determining of the factors or features includes using machine learning or multivariate statistical techniques.
15 . The method of claim 12 , the operations further comprising returning the second construct of n-dimensional space information to the first construct of n-dimensional space information using the one or more mathematical transformation functions.
16 . The method of claim 12 , wherein the analysis further includes building a phylogenetic tree using aligned sequences matched to the one or more samples.
17 . The method of claim 12 , wherein each of the one or more strains has a different molecular function.
18 . The method of claim 12 , wherein the one or snore censuses are obtained over one or more time points.
19 . The method of claim 18 , wherein the second construct includes a plot that visualizes patterns corresponding to the one or more samples over a time period corresponding to the one or more time points.
20 . The method of claim 12 ,-herein the microorganisms include components other than bacteria and archaea.
21 . The method of claim 12 , wherein the generating of the microbiome information includes deriving the microbiome information from one or more fragments of any genetic material detected in the one or more samples.