An incremental author disambiguation framework may create new clusters to accommodate new data based on the existing cluster results and newly added data. The proposed system may provide frequent update of taxonomic classification, name disambiguation and many other applications because it takes less time to generate new results. In addition, the proposed methods may reduce the time needed for updating the model and help improve the performance with the limited computational resource.

A method, computer program product, and computing system for visual diarization of an encounter is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to: associate a first portion of the encounter information with a first encounter participant, and associate at least a second portion of the encounter information with at least a second encounter participant. A visual representation of the encounter information is rendered. A first visual representation of the first portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information. At least a second visual representation of the at least a second portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information.

A method, computer program product, and computing system for visual diarization of an encounter is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to: associate a first portion of the encounter information with a first encounter participant, and associate at least a second portion of the encounter information with at least a second encounter participant. A visual representation of the encounter information is rendered. A first visual representation of the first portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information. At least a second visual representation of the at least a second portion of the encounter information is rendered that is temporally-aligned with the visual representation of the encounter information.

A method for stream-processing biomedical data includes registering, by a file system, with an operating system kernel of the computing device, as a file handler for files requested from a file system mount directory. The file system receives a first request for access to at least a first portion of a file stored on a remotely located storage device and receives a second request for access to at least a second portion of the file. The file system forwards the first request and the second request to a pre-fetching component, which determines whether the first request and the second request are associated with a sequential read operation. The pre-fetching component automatically retrieves a third portion of the requested file, before receiving a third request for the file, based on a determination that the first request and the second request are associated with the sequential read operation.

A method for stream-processing biomedical data includes registering, by a file system, with an operating system kernel of the computing device, as a file handler for files requested from a file system mount directory. The file system receives a first request for access to at least a first portion of a file stored on a remotely located storage device and receives a second request for access to at least a second portion of the file. The file system forwards the first request and the second request to a pre-fetching component, which determines whether the first request and the second request are associated with a sequential read operation. The pre-fetching component automatically retrieves a third portion of the requested file, before receiving a third request for the file, based on a determination that the first request and the second request are associated with the sequential read operation.

Provided herein are automated apparatus and methods for the identification of microorganisms in various samples. The disclosure solves existing challenges encountered in identifying and distinguishing various types of microorganisms, including viruses and bacteria in a timely, efficient, and automated manner by library preparation and sequencing.

Provided is an engineered antimicrobial peptide. Also provided is a composition comprising an engineered antimicrobial peptide. Provided is a method of treating a subject in need thereof, comprising administering a therapeutically effective amount of a composition comprising an engineered antimicrobial peptide. Also provided is a method of producing an engineered antimicrobial peptide.

Provided is an engineered antimicrobial peptide. Also provided is a composition comprising an engineered antimicrobial peptide. Provided is a method of treating a subject in need thereof, comprising administering a therapeutically effective amount of a composition comprising an engineered antimicrobial peptide. Also provided is a method of producing an engineered antimicrobial peptide.

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.