Abstract: A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which maybe a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which may be a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: Examples are disclosed herein that relate to integrating health data and calendar data of one or more users and providing insights for a selected user to help the user accomplish an outcome of interest. The insights may be identified based on a group of cohorts determined to be similar to the selected user and/or used to predict a likelihood that the selected user will achieve an outcome of interest. Additional insights may be provided by monitoring an effect that following a recommendation has on the selected user achieving the outcome of interest. Recommendations and/or updates to recommendations may be provided based on the insights.

Abstract: Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

Abstract: A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which may be a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which maybe a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: A composition as disclosed is comprised of a plurality of particles and a pharmaceutically acceptable carrier. The particles are comprised of (1) an adjuvant; (2) a biocompatible polymer which maybe a co-polymer such as PLGA, and (3) a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. The carrier includes an adjuvant such as a monophosphoryl lipid A (MPL) different from the adjuvant in the particles. The particles may be sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: Described herein are technologies pertaining to computationally-efficiently performing genome-wide association studies. Feature selection methods are used to identify genetic markers for addressing potential confounding in the data. Then, single SNPs, or groups of genetic markers are analyzed to ascertain whether such groups are causal or tagging of causal as to a specified phenotype, after taking in to account the feature-selected SNPs. Group and univariate analysis is accomplished by way of analyzing a group of genetic markers conditioned upon other genetic markers that are found to be predictive of the specified phenotype.

Abstract: Described herein are technologies pertaining to predicting whether a living being, such as a human being, an animal, or a plant, has a phenotype or set of phenotypes in real-time or near real-time. A filter set of genetic markers are determined heuristically, by first univariately computing scores for respective genetic markers that are indicative of their predictive ability with respect to the phenotype or the set of phenotypes. Thereafter, during training, the filter set is initially selected and thereafter expanded based upon the scores, until predictive accuracy for the phenotype or set of phenotypes reaches a threshold or is optimized. The filter set, which includes a relatively small number of genetic markers, is subsequently employed for real-time or near-real time phenotype prediction.

Abstract: A computer-executable algorithm that estimates parameters of a predictive model in computation time of less than O(n2k2) when k<=n, is described herein, wherein n is a number of data items considered when estimating the parameters of the predictive model and k is a number of features of each data item considered when estimating the parameters of the predictive model. The parameters are estimated to maximize the probability of observing target values in the training data given the features considered in the training data.

Abstract: A system described herein includes a receiver component that receives an HLA data set, wherein the HLA data set comprises low resolution HLA data. An HLA refinement component comprises a statistical model that automatically refines the HLA data set to transform the low resolution HLA data to high resolution HLA data.

Abstract: A composition as disclosed is comprised of a plurality of groups of particles. The particles are comprised of a biocompatible polymer which maybe a co-polymer such as PLGA combined with a peptide of a sequence of interest, e.g. a sequence which corresponds to a sequence presented on a surface of a cell infected with a virus. A plurality of different groups of particles are provided in the formulation wherein the particles within any single group include peptides of identical amino acid sequence. The particles are sized such that they are sufficiently large so as to prevent more than the contents of a single particle from being presented to a single immune system cell.

Abstract: Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

Abstract: A system described herein includes a receiver component that receives an HLA data set, wherein the HLA data set comprises low resolution HLA data. An HLA refinement component comprises a statistical model that automatically refines the HLA data set to transform the low resolution HLA data to high resolution HLA data.

Abstract: The present invention includes a system and a method for processing large data sets that are too large to conveniently fit into a formal database application. The large data set processing system and method use a prediction model having a feature selection capability to process a fraction of the large data set and define useful predictors. The useful features are used to make predictions for the entire data set. The large data set processing system includes a useful predictor module, for defining useful predictors, and a feature-selection prediction model, for processing a portion of the data set (including the useful predictors) to obtain prediction results.

Abstract: The present invention includes a system and a method for processing large data sets that are too large to conveniently fit into a formal database application. The large data set processing system and method use a prediction model having a feature selection capability to process a fraction of the large data set and define useful predictors. The useful features are used to make predictions for the entire data set. The large data set processing system includes a useful predictor module, for defining useful predictors, and a feature-selection prediction model, for processing a portion of the data set (including the useful predictors) to obtain prediction results.

Abstract: Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

Abstract: Systems and methods are provided for producing displays of the accuracy of data mining or statistical models that produce associative predictions. For all cases in a testing data set, the model makes predictions and provides associated probabilities. The cases are sorted by their probability of making accurate predictions and a graph is made of the accuracy of the model over various subsets containing the highest probability cases as evaluated by the model. Where a number of probabilities are presented for the predictions in a basket of predictions, those probabilities are combined to yield a probability score for the entire basket. Additionally, the accuracy of a model over different basket sizes may be graphed. The accuracy graph may also be produced for any models making a prediction, by graphing the probability of making accurate predictions and a graph made of the accuracy of the model over various subsets of the data containing the highest probability cases.

Abstract: Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

Abstract: The present invention includes a system and a method for processing large data sets that are too large to conveniently fit into a formal database application. The large data set processing system and method use a prediction model having a feature selection capability to process a fraction of the large data set and define useful predictors. The useful features are used to make predictions for the entire data set. The large data set processing system includes a useful predictor module, for defining useful predictors, and a feature-selection prediction model, for processing a portion of the data set (including the useful predictors) to obtain prediction results.