Abstract: Provided herein are methods for identifying subsequences in a sample. The methods may comprise contacting an analyte with a binding moiety, bringing the analyte in contact with a first detection probe and second detection probe, wherein the first detection probe and second detection probe are adjacent and different from one another, detecting the corresponding detection moieties, and using the identified subsequences to identify the analyte.

Abstract: Provided herein are methods, compositions, and systems that may be useful for the detection of one or more analytes within a biological sample. The methods may comprise providing a cell. The cell may comprise an analyte. The method may comprise contacting the cell with a binding moiety. The binding moiety may recognize and/or bind to the analyte. The method may comprise contacting the binding moiety or derivative thereof with a detection probe to form a complex. The complex may be detected using an imaging system. A signal of the complex may be detected. The signal may have a full width at half maximum.

Abstract: The present disclosure provides a methods and systems for analyzing one or more samples. The method may comprise using a plurality of sensors to substantially continuously integrate through a plurality of object planes of the sample. The integration can then generate a volumetric measurement of the sample.

Abstract: The present disclosure provides a methods and systems for analyzing one or more samples. The method may comprise using a plurality of sensors to substantially continuously integrate through a plurality of object planes of the sample. The integration can then generate a volumetric measurement of the sample.

Abstract: The present disclosure provides a methods and systems for analyzing one or more samples. The method may comprise using a plurality of sensors to substantially continuously integrate through a plurality of object planes of the sample. The integration can then generate a volumetric measurement of the sample.

Abstract: Provided herein are methods and systems for identifying a proximity of analytes in a sample. The method may comprise contacting one or more analytes with one or more probes. The proximity of the one or more analytes to each other may cause a ligation event between the one or more probes. An amplification reaction may be performed comprising one or more copies of a barcode or derivative thereof. The one or more copies of the barcode or derivative thereof may be detected to identify a proximity between the one or more analytes.

Abstract: Provided herein are methods and systems for identifying a proximity of analytes in a sample. The method may comprise contacting one or more analytes with one or more probes. The proximity of the one or more analytes to each other may cause a ligation event between the one or more probes. An amplification reaction may be performed comprising one or more copies of a barcode or derivative thereof. The one or more copies of the barcode or derivative thereof may be detected to identify a proximity between the one or more analytes.

Abstract: A method and an apparatus for generating an image processing interface, a device, and a storage medium, including: receiving a first instruction, where the first instruction is used to characterize an image parameter of a target image; determining an image template corresponding to the first instruction, where the image template is used to characterize a processing flow of the target image; and generating a processing interface of the target image according to the image template. Since the image template standardizes the process and steps of image processing, the specific operation steps for generating an image processing interface are simplified, while standardizing the generated image processing interface, reducing the using and maintenance cost of the image processing interface, and improving the security of the image processing interface.

Abstract: A multivariable analysis tool is provided wherein an orthogonal decomposition method such as a Partial Least Squares algorithm is applied to a disturbance model, which relates the known loop disturbances to the loop model residue. The tool according to the invention first extracts the most dominant correlation to the loop model residue and then uses the residue to search for secondary dominant correlation in an orthogonal space, and repeats this process until no further output variation can be significantly attributed by the next dominant correlation. In this way, the analysis tool of the present invention is able to estimate the performance potential of each control loop under different disturbance conditions and provide a control performance index by comparing the achieved performance to the performance potential in a multi-variable environment. This index indicates whether or not a given loop is under optimal operation and shows variance of the loop from the best achievable loop performance.

Abstract: A multivariable analysis tool is provided wherein an orthogonal decomposition method such as a Partial Least Squares algorithm is applied to a disturbance model, which relates the known loop disturbances to the loop model residue. The tool according to the invention first extracts the most dominant correlation to the loop model residue and then uses the residue to search for secondary dominant correlation in an orthogonal space, and repeats this process until no further output variation can be significantly attributed by the next dominant correlation. In this way, the analysis tool of the present invention is able to estimate the performance potential of each control loop under different disturbance conditions and provide a control performance index by comparing the achieved performance to the performance potential in a multi-variable environment. This index indicates whether or not a given loop is under optimal operation and shows variance of the loop from the best achievable loop performance.