A method for using genomic data to locate a reservoir is provided. The method includes collecting samples in a field over a reservoir. A genomic analysis is performed on the samples to obtain genomic data. The genomic data is clustered to classify sequences of microbial communities associated with using hydrocarbons for energy. The genomic data is used in an artificial intelligence model to identify a drilling site for hydrocarbon production.

A method for using genomic data to locate a reservoir is provided. The method includes collecting samples in a field over a reservoir. A genomic analysis is performed on the samples to obtain genomic data. The genomic data is clustered to classify sequences of microbial communities associated with using hydrocarbons for energy. The genomic data is used in an artificial intelligence model to identify a drilling site for hydrocarbon production.

A system and method for estimation of functional potential of pathways in genomes/meta-genomes is provided. Initially seed modules are identified and a multi-dimensional tag map is created. Further, pathway annotation is done using a novel 6Q annotation step. Hidden Markov Model (HMM) based search augmented with an analysis of gene context is used to refine the modules using a graph theory based approach. The method uses the multidimensional module tag map to build a backend knowledge base and use the same for an iterative literature search to verify the clustered organization of genes within a pathway. Finally, a score is assigned to compute the contribution of each pathway within the genome/meta-genome.

A system and method for estimation of functional potential of pathways in genomes/meta-genomes is provided. Initially seed modules are identified and a multi-dimensional tag map is created. Further, pathway annotation is done using a novel 6Q annotation step. Hidden Markov Model (HMM) based search augmented with an analysis of gene context is used to refine the modules using a graph theory based approach. The method uses the multidimensional module tag map to build a backend knowledge base and use the same for an iterative literature search to verify the clustered organization of genes within a pathway. Finally, a score is assigned to compute the contribution of each pathway within the genome/meta-genome.

A method and apparatus are provided for designing sequence-defined biomolecules, such as proteins using a data-driven, evolution-based process. To design proteins, an iterative method founded on a combination of an unsupervised sequence-based model with a supervised functionality-based model can select candidate amino acid sequences that are likely to have a desired functionality. Feedback from measuring the candidate proteins using a high-throughput gene-synthesis and a protein screening process is used to refine and improve the models guiding the candidate selection to the most promising regions of the very large amino acid sequence search space.

A method and apparatus are provided for designing sequence-defined biomolecules, such as proteins using a data-driven, evolution-based process. To design proteins, an iterative method founded on a combination of an unsupervised sequence-based model with a supervised functionality-based model can select candidate amino acid sequences that are likely to have a desired functionality. Feedback from measuring the candidate proteins using a high-throughput gene-synthesis and a protein screening process is used to refine and improve the models guiding the candidate selection to the most promising regions of the very large amino acid sequence search space.

Pharmacogenomic (PGx) testing provides valuable insight into patient-specific mechanisms for drug response. Limitations on the throughput of PGx testing and associated costs make it currently infeasible to test every individual, particularly in large medical enterprises such as the VA or medical centers servicing large numbers of patients simultaneously. To overcome this, a method and system is described that predicts whether a patient is likely to benefit from PGx testing. Our method permits a healthcare provider to prioritize patients for PGx testing based on which patients are identified as being most likely to benefit from the testing, and can avoid PGx testing for those patients that are likely to obtain little or no benefit from the testing, thereby saving healthcare costs.

Described herein is a novel alignment method which leverages multi-stage secondary analysis, with each stage progressively reducing the amount of data to be analyzed in the next stage(s), but increasing exhaustiveness of the search on the remaining data received from previous stage(s). This way, less noisy alignments can be quickly identified from the initially large data-pools in early stage(s), while very noisy alignments can be identified equally fast from smaller data-pools in latter stage(s) of computation, thus maintaining target sensitivity while reducing overall compute times.

Described herein is a novel alignment method which leverages multi-stage secondary analysis, with each stage progressively reducing the amount of data to be analyzed in the next stage(s), but increasing exhaustiveness of the search on the remaining data received from previous stage(s). This way, less noisy alignments can be quickly identified from the initially large data-pools in early stage(s), while very noisy alignments can be identified equally fast from smaller data-pools in latter stage(s) of computation, thus maintaining target sensitivity while reducing overall compute times.

Displaying an indication of ancestral data is disclosed. An indication that a genetic interval corresponds to a reference interval that has a likelihood of having one or more ancestral origins is received. One or more graphic display parameters are determined based at least in part on the indication. An indication of the one or more ancestral origins is visually displayed using the one or more graphic display parameters.