Provided herein are methods and systems of molecular profiling of diseases, such as cancer. In some embodiments, the molecular profiling can be used to identify treatments for a disease, such as treatments that were not initially identified as a treatment for the disease or not expected to be a treatment for a particular disease.

Provided herein are methods and systems of molecular profiling of diseases, such as cancer. In some embodiments, the molecular profiling can be used to identify treatments for a disease, such as treatments that were not initially identified as a treatment for the disease or not expected to be a treatment for a particular disease.

There are provided methods, systems and processes for the utilization of microbial and related genetic information for use in the exploration, determination, production and recovery of natural resources, including energy sources, and the monitoring, control and analysis of processes and activities.

There are provided methods, systems and processes for the utilization of microbial and related genetic information for use in the exploration, determination, production and recovery of natural resources, including energy sources, and the monitoring, control and analysis of processes and activities.

This disclosure relates to generating interactive graphical visualisations of clinical and genetic data. A processor receives the clinical data indicative of observed phenotypes, accesses a database to determine associations of the observed phenotypes with disorders and accesses a second database to determine associations between the disorders and genetic properties. The processor then determines an association value for each combination of the observed phenotypes and the genetic properties based on a number of paths between them. The processor also generates a graphical user interface, comprising an arrangement of the association values and a user control element associated with the phenotypes and/or the genetic properties. Finally, upon detecting user interaction in relation to the user control element, the processor re-arranges the arrangement of the association values in the graphical user interface to reflect the detected user interaction.

This disclosure relates to generating interactive graphical visualisations of clinical and genetic data. A processor receives the clinical data indicative of observed phenotypes, accesses a database to determine associations of the observed phenotypes with disorders and accesses a second database to determine associations between the disorders and genetic properties. The processor then determines an association value for each combination of the observed phenotypes and the genetic properties based on a number of paths between them. The processor also generates a graphical user interface, comprising an arrangement of the association values and a user control element associated with the phenotypes and/or the genetic properties. Finally, upon detecting user interaction in relation to the user control element, the processor re-arranges the arrangement of the association values in the graphical user interface to reflect the detected user interaction.

Methods, systems, and computer-readable media for processing spatially related sequence data received from a sequencing device are presented. In one or more embodiments, a computing platform may receive, from a sequencing device, image data associated with a sample. The computing platform may identify, based on the image data received from the sequencing device, a first sequence located at first spatial coordinates. Subsequently, the computing platform may store, in a spatially searchable database, a first data element comprising the first spatial coordinates and a first identifier corresponding to the first sequence to spatially relate the first sequence to other sequences present in the sample. In some instances, the image data received from the sequencing device may include spatial information, temporal information, and color information associated with the sample, and the computing platform may present, on a display device, information identifying a presence of the first sequence at the first spatial coordinates.

Methods, systems, and computer-readable media for processing spatially related sequence data received from a sequencing device are presented. In one or more embodiments, a computing platform may receive, from a sequencing device, image data associated with a sample. The computing platform may identify, based on the image data received from the sequencing device, a first sequence located at first spatial coordinates. Subsequently, the computing platform may store, in a spatially searchable database, a first data element comprising the first spatial coordinates and a first identifier corresponding to the first sequence to spatially relate the first sequence to other sequences present in the sample. In some instances, the image data received from the sequencing device may include spatial information, temporal information, and color information associated with the sample, and the computing platform may present, on a display device, information identifying a presence of the first sequence at the first spatial coordinates.

First and second sequenced outputs are accessed. The sequenced outputs contain variants occurring at different carriers and at different carrier positions. Hashes are generated over a selected pattern length of positions for those carrier positions that are shared between the sequenced outputs to produce window hashes for base patterns in first and second sequences. Each sequence is based on the shared carrier positions and the respective sequenced output. The window hashes are non-unique. Window hashes that occur less than a ceiling number times are selected. The selected window hashes are compared between the sequences on a starting position basis such that selected window hashes for base patterns having same start positions in the sequenced outputs are compared. Common window hashes are identified between the sequences based on the comparing. A similarity measure is determined between the sequences based on the common window hashes.

First and second sequenced outputs are accessed. The sequenced outputs contain variants occurring at different carriers and at different carrier positions. Hashes are generated over a selected pattern length of positions for those carrier positions that are shared between the sequenced outputs to produce window hashes for base patterns in first and second sequences. Each sequence is based on the shared carrier positions and the respective sequenced output. The window hashes are non-unique. Window hashes that occur less than a ceiling number times are selected. The selected window hashes are compared between the sequences on a starting position basis such that selected window hashes for base patterns having same start positions in the sequenced outputs are compared. Common window hashes are identified between the sequences based on the comparing. A similarity measure is determined between the sequences based on the common window hashes.