Abstract: Methods for analyzing omics data and using the omics data to determine genetic distances and/or difference scores among a plurality of biological samples to so further determine the homogeneity of a group having a plurality of biological samples and/or exclude an individual biological sample from a group of biological samples as an outlier are presented. In preferred methods, a plurality of local differential string sets among the plurality of sequence strings is generated using a plurality of local alignments. The local different string is an indicative of genetic difference between one sequence string and one of the rests of the sequence strings among the plurality of sequence strings. From the plurality of local differential string sets, a plurality of difference scores among the plurality of sequence strings can be determined.

Abstract: Contemplated antiviral/cancer treatments comprise analysis of neoepitopes from viral DNA that has integrated into the host genome, and design of immunotherapeutic agents against such neoepitopes.

Abstract: Methods for analyzing omics data and using the omics data to determine genetic distances and/or difference scores among a plurality of biological uncles to so further determine the homogeneity of a group having a plurality of biological samples and/or exclude as individual biological sample from a group of biological samples a an outlier we presented. In preferred methods, a plurality of local differential string sea among do plurality of sequence strings is generated wing a plurality of local alignments. The local different suing is as indicative of genetic difference between one sequence string and one of do rests of do sequence strings among the plurality of sequence strings. From the plurality of local differential string sets, a plurality of difference scores among do plurality of sequence strings can be determined.

Abstract: Contemplated antiviral/cancer treatments comprise analysis of neoepitopes from viral DNA that has integrated into the host genome, and design of immunotherapeutic agents against such neoepitopes.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.

Abstract: Various devices, systems, structures and methods are disclosed related to securely authorizing a transaction by synchronizing digital genomic data with associated synthetic genomic variants. An embodiment of the present invention utilizes digital genomic data associated with an entity, such as a person, who may utilize a genome-based security device to complete a transaction. In one embodiment, a person may use a genome-based security device to communicate with an external device over a wireless or other communication interface, synchronize digital genomic data and an associated synthetic variant received from the external device with digital genomic data and associated synthetic variant stored on the genome-based security device.

Abstract: Techniques are provided for determining a cell count within a whole slide pathology image. The image is segmented using a global threshold value to define a tissue area. A plurality of patches comprising the tissue area are selected. Stain intensity vectors are determined within the plurality of patches to generate a stain intensity image. The stain intensity image is iteratively segmented to generate a cell mask using a local threshold value that is and gradually reduced after each iteration. A chamfer distance transform is applied to the cell mask to generate a distance map. Cell seeds are determined on the distance map. Cell segments are determined using a watershed transformation, and a whole cell count is calculated for the plurality of patches based on the cell segments. A client device may be configured for real-time cell counting based on the whole cell count.

Abstract: Techniques are provided for determining classifications based on WSIs. A varied-size feature map is generated for each training WSI by generating a grid of patches for the training WSI, segmenting the training WSI into tissue and non-tissue areas, and converting patches comprising the tissue areas into tensors. Bounding boxes are generated based on the patches comprising tissue areas and segmented into feature map patches. A fixed-size feature map is generated based on a subset of the feature map patches. A classifier model is trained to process fixed-size feature maps corresponding to the training WSIs such that, for each fixed-size feature map, the classifier model is operable to assign a WSI-level tissue or cell morphology classification or regression based on the tensors. A classification engine is configured to use the trained classifier model to determine a WSI-level tissue or cell morphology classification or regression for a test WSI.

Abstract: A computer implemented method of generating at least one shape of a region of interest in a digital image is provided.

Abstract: A method of determining a region of interest in an image of tissue of an individual by an apparatus including processing circuitry may include executing, by the processing circuitry, instructions that cause the apparatus to partition an image of tissue of an individual into a set of areas, identify a tissue type of each area of the image, and apply a classifier to the image to determine a region of interest, the classifier being configured to determine regions of interest based on the tissue types of the set of areas of the image.

Abstract: RNA from a biological fluid is stabilized during isolation and/or storage using DNA. In especially preferred aspects, the RNA is cfRNA and/or ctRNA, and the biological fluid is blood.

Abstract: Contemplated systems and methods use identification and classification of somatic single nucleotide variants found in a primary tumor and metastases to determine phylogeny of the metastases.

Abstract: Techniques are provided for determining a cell count within a whole slide pathology image. The image is segmented using a global threshold value to define a tissue area. A plurality of patches comprising the tissue area are selected. Stain intensity vectors are determined within the plurality of patches to generate a stain intensity image. The stain intensity image is iteratively segmented to generate a cell mask using a local threshold value that is and gradually reduced after each iteration. A chamfer distance transform is applied to the cell mask to generate a distance map. Cell seeds are determined on the distance map. Cell segments are determined using a watershed transformation, and a whole cell count is calculated for the plurality of patches based on the cell segments. A client device may be configured for real-time cell counting based on the whole cell count.

Abstract: Techniques are provided for determining classifications based on WSIs. A varied-size feature map is generated for each training WSI by generating a grid of patches for the training WSI, segmenting the training WSI into tissue and non-tissue areas, and converting patches comprising the tissue areas into tensors. Bounding boxes are generated based on the patches comprising tissue areas and segmented into feature map patches. A fixed-size feature map is generated based on a subset of the feature map patches. A classifier model is trained to process fixed-size feature maps corresponding to the training WSIs such that, for each fixed-size feature map, the classifier model is operable to assign a WSI-level tissue or cell morphology classification or regression based on the tensors. A classification engine is configured to use the trained classifier model to determine a WSI-level tissue or cell morphology classification or regression for a test WSI.

Abstract: A method of determining a region of interest in an image of tissue of an individual by an apparatus including processing circuitry may include executing, by the processing circuitry, instructions that cause the apparatus to partition an image of tissue of an individual into a set of areas, identify a tissue type of each area of the image, and apply a classifier to the image to determine a region of interest, the classifier being configured to determine regions of interest based on the tissue types of the set of areas of the image.

Abstract: Contemplated systems and methods use identification and classification of somatic single nucleotide variants found in a primary tumor and metastases to determine phylogeny of the metastases.

Abstract: Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.

Abstract: Systems and methods for prediction of the treatment outcome for immune therapy are presented in which omics data of a patient tumor sample are used. Most typically, the omics data are processed to identify mutational signatures (especially APOBEC/POLE signatures), immune checkpoint expression, and MSI status as leading indicators to predict the treatment outcome for immune therapy. Such prediction advantageously integrates various parameters that would otherwise, when individually considered, skew prediction outcome.

Abstract: Methods for analyzing omics data and using the omics data to determine prognosis of a cancer, to predict an outcome of a treatment, and/or to determine an effectiveness of a treatment are presented. In preferred methods, blood from a patient having a cancer or suspected to have a cancer is obtained and blood omics data for a plurality of cancer-related, inflammation-related, or DNA repair-related genes are obtained. A cancer score can be calculated based on the omics data, which then can be used to provide a cancer prognosis, a therapeutic recommendation, an effectiveness of a treatment.

Abstract: Circulating free RNA (cfRNA) is used for monitoring status and/or treatment response for neural tumors, and especially glioma, glioblastoma, and neuroblastoma. Particularly preferred cfRNAs include those that encode a marker that is specific to a neural tumor, but also markers that are specific to DNA repair status and/or immune status.