Emc IP Holding Company LLC

Arnon Benshahar

Patricia Gomes Soares Florissi

Michal Ziv Ukelson

Ran Dach

Ehud Gudes

An apparatus in one embodiment comprises a distributed data processing system in which multiple processing devices communicate with one another over at least one network. The distributed data processing system is configured to obtain reads of biological samples of respective sample sources, with each of the biological samples containing genomic material from a plurality of distinct microorganisms within an environment of a corresponding one of the sample sources, and to perform distributed data analytics to provide surveillance functionality characterizing at least one of a disease, an infection and a contamination as involving genomic material from multiple ones of the sample source. Performing distributed data analytics illustratively comprises performing local analytics in respective ones of a plurality of data zones, and performing global analytics utilizing results of the local analytics performed in the respective data zones.

Distributed data analytics

An apparatus in one embodiment comprises a distributed data processing system in which multiple processing devices communicate with one another over at least one network. The distributed data processing system is configured to obtain reads of biological samples of respective sample sources, with each of the biological samples containing genomic material from a plurality of distinct microorganisms within an environment of a corresponding one of the sample sources, and to perform distributed data analytics to characterize an actual or potential outbreak of at least one of a disease, an infection and a contamination that involves genomic material from multiple ones of the distinct microorganisms in one or more of the sample sources. Performing distributed data analytics illustratively comprises performing local analytics in respective ones of a plurality of data zones, and performing global analytics utilizing results of the local analytics performed in the respective data zones.

A method comprises configuring a first metagenomics sequencing center to perform metagenomics sequencing on a first set of biological samples, and processing metagenomics sequencing results from the first metagenomics sequencing center with additional metagenomics sequencing results from one or more other metagenomics sequencing centers for respective additional sets of biological samples in conjunction with associated epidemiological data accessible to respective ones of the first and additional metagenomics sequencing centers. The processing is configured to generate global view information characterizing epidemiological relationships between the metagenomics sequencing results from the first and additional metagenomics sequencing centers. The method further includes providing the global view information to a requesting client.

Method and apparatus for providing global view information to a client

An apparatus in one embodiment comprises a distributed data processing system in which multiple processing devices communicate with one another over at least one network. The distributed data processing system is configured to obtain reads of biological samples of respective microbiomes, with each of the biological samples containing genomic material from a plurality of distinct microorganisms of its corresponding one of the microbiomes, and to perform distributed data analytics to detect a disease, infection or contamination that involves genomic material from multiple ones of the distinct microorganisms in one or more of the microbiomes. Performing distributed data analytics illustratively comprises performing local analytics in respective ones of a plurality of data zones, and performing global analytics utilizing results of the local analytics performed in the respective data zones. Each of the data zones may comprise, for example, one or more sequencing centers utilized to generate a corresponding subset of the reads within that data zone.

A method comprises receiving metagenomics data, configuring a data model characterizing relationships between aspects of the metagenomics data, and processing the metagenomics data in accordance with the configured data model in order to characterize at least one of a disease, infection or contamination. The data model comprises an abundance score element that relates portions of the metagenomics data comprising reads of biological samples to one or more genomic sequences of an ecogenome, and a comparative score element that relates portions of the metagenomics data comprising characteristics of multiple patients to one another with respect to the disease, infection or contamination. The data model further relates the abundance score element to the comparative score element via one or more additional elements of the data model corresponding to respective other aspects of the metagenomics data. The metagenomics data may comprise metagenomics sequencing results from metagenomics sequencing centers associated with respective data zones.

Methods and apparatus implementing data model for disease monitoring, characterization and investigation

A method comprises processing metagenomics sequencing results from a plurality of metagenomics sequencing centers associated with respective data zones, configuring a data model based at least in part on the metagenomics sequencing results, performing one or more reasoning operations over the data model to infer relationships between entities of the data model that are not directly expressed by the data model, and updating the data model based at least in part on the inferred relationships. The method further comprises repeating the processing, configuring, performing and updating for additional metagenomics sequencing results from one or more of the metagenomics sequencing centers. One or more portions of the data model illustratively comprise respective profiles each characterizing at least one of a disease, infection or contamination based at least in part on the metagenomics sequencing results.

Reasoning on data model for disease monitoring, characterization and investigation

A method comprises configuring a first processing node for communication with one or more additional processing nodes and with one or more of a plurality of geographically-distributed metagenomics sequencing centers via one or more networks, processing metagenomics sequencing results obtained from one or more of the metagenomics sequencing centers in the first processing node, and providing surveillance functionality relating to at least one designated biological issue on behalf of one or more requesting clients based at least in part on the processing of metagenomics sequencing results performed by the first processing node and related processing performed by one or more of the additional processing nodes. Each of the metagenomics sequencing centers is configured to perform metagenomics sequencing on biological samples from respective sample sources in a corresponding data zone.

Distributed data processing platform for metagenomic monitoring and characterization

A method comprises obtaining results of metagenomics sequencing performed on biological samples from respective sample sources, generating hit abundance score vectors for respective ones of the samples based at least in part on the metagenomics sequencing results, obtaining epidemiological data relating to at least one of a disease, infection or contamination characterized by one or more of the hit abundance score vectors, and generating patient comparative indexes based at least in part on the epidemiological data. The method further comprises obtaining one or more Big Data profiles relating to one or more of the hit abundance score vectors and one or more of the comparative indexes, and providing surveillance functionality utilizing a combination of the hit abundance score vectors and the patient comparative indexes based at least in part on information derived from the one or more Big Data profiles.

Metagenomics-based biological surveillance system using big data profiles

A method comprises obtaining results of metagenomics sequencing performed on biological samples from respective sample sources, identifying particular ones of the biological samples that are related to a disease, infection or contamination based at least in part on the results of metagenomics sequencing, generating a genomic comparison component comprising hit abundance score vectors for respective ones of the identified samples, generating an epidemiologic comparison component comprising a graph in which nodes corresponding to patients are connected in the graph based at least in part on patient comparative indexes, collectively processing portions of the genomic comparison component with portions of the epidemiologic comparison component to further characterize the disease, infection or contamination, and updating a profile of the disease, infection or contamination based at least in part on the further characterization.

Growing community of inventors

Tel Aviv, Israel

Arnon Benshahar