Abstract: A method for processing biopolymer arrays and apparatus and computer program products for executing the method. The method may include reading a different array identifier for each biopolymer array from a tag associated with that array. At least some of the biopolymer arrays are read and results from each read array saved in a memory linked with the read identifier for that array. Different communication addresses and a selection of an array identifier for each, are received. For at least some of the arrays, the saved results for each are matched with one of the different communication addresses using the identifier, and the saved results transmitted for those arrays to the matched different communication addresses. A method of processing data from the reading of biopolymer arrays is also provided.

Abstract: A method for processing biopolymer arrays and apparatus and computer program products for executing the method. The method may include reading a different array identifier for each biopolymer array from a tag associated with that array. At least some of the biopolymer arrays are read and results from each read array saved in a memory linked with the read identifier for that array. Different communication addresses and a selection of an array identifier for each, are received. For at least some of the arrays, the saved results for each are matched with one of the different communication addresses using the identifier, and the saved results transmitted for those arrays to the matched different communication addresses. A method of processing data from the reading of biopolymer arrays is also provided.

Abstract: A system and method of operating a data processing system to provide feature extraction from an image obtained from a plurality of chemical arrays is disclosed. The method includes bifurcating processing of the image by performing image processing and post-processing. The image processing includes processing parts of the image, each part corresponding to a different one of the arrays, in an automated batch process, to produce image-processed outputs that are different from the image and contain information extracted from the image. The post-processing includes processing the image-processed outputs according to different post-processing protocols with respect to different ones of those parts of the image corresponding to at least two of the arrays, to produce post-processed outputs. The method includes outputting at least one of the image-processed outputs and/or at least one of the post-processed outputs.

Abstract: Feature locations are determined in an array image obtained from reading a chemical array comprising multiple features arranged in a polygon and which array optionally includes sub-arrays within the array. A complete image of the array or a sub-array is presented on a display. Magnified images of corner regions of the displayed complete image are simultaneously presented on the display with the complete image. A user selection of corners for the array or sub-array are received and an array or sub-array actual outline is generated by linearly connecting the user selected corners. The generated actual outline is presented on the magnified image and may also be simultaneously presented on the complete image. Feature locations in the array or sub-array image may be determined based on the actual outline.

Abstract: Feature locations are determined in an array image obtained from reading a chemical array comprising multiple features arranged in a polygon and which array optionally includes sub-arrays within the array. A complete image of the array or a sub-array is presented on a display. Magnified images of corner regions of the displayed complete image are simultaneously presented on the display with the complete image. A user selection of corners for the array or sub-array are received and an array or sub-array actual outline is genereated by linearly connecting the user selected corners. The generated actual outline is presented on the magnified image and may also be simultaneously presented on the complete image. Feature locations in the array or sub-array image may be determined based on the actual outline.

Abstract: A method for processing biopolymer arrays and apparatus and computer program products for executing the method. The method may include reading a different array identifier for each biopolymer array from a tag associated with that array. At least some of the biopolymer arrays are read and results from each read array saved in a memory linked with the read identifier for that array. Different communication addresses and a selection of an array identifier for each, are received. For at least some of the arrays, the saved results for each are matched with one of the different communication addresses using the identifier, and the saved results transmitted for those arrays to the matched different communication addresses. A method of processing data from the reading of biopolymer arrays is also provided.

Abstract: A method and system for normalizing two or more molecular array data sets. Input molecular array data sets are separately globally normalized by, for example, dividing the feature-signal magnitudes of each data set by the geometric mean of the feature-signal magnitudes of the data set. The globally normalized feature signal magnitudes within each data set are ranked in ascending order. A numeric function is created that relates feature-signal magnitudes of the data sets. Only a subset of the features, obtained by selecting features that are similarly ranked in the separate feature-signal-magnitude rankings for the data sets, is used to construct the numeric function. The numeric function is smoothed by one of many possible different smoothing procedures.

Abstract: A method and system for normalizing two or more molecular array data sets. Input molecular array data sets are separately globally normalized by, for example, dividing the feature-signal magnitudes of each data set by the geometric mean of the feature-signal magnitudes of the data set. The globally normalized feature signal magnitudes within each data set are ranked in ascending order. A numeric function is created that relates feature-signal magnitudes of the data sets. Only a subset of the features, obtained by selecting features that are similarly ranked in the separate feature-signal-magnitude rankings for the data sets, is used to construct the numeric function. The numeric function is smoothed by one of many possible different smoothing procedures.