Abstract: Disclosed herein are methods for selecting tumor-specific neoantigens from a tumor of a subject that are suitable for subject-specific immunogenic compositions.

Abstract: Described is a system and method that determines character sequences from speech, without determining the words of the speech, and processes the character sequences to determine sentiment data indicative of emotional state of a user that output the speech. The emotional state may then be presented or provided as an output to the user.

Abstract: Systems, devices, and methods are provided for detecting and correcting eating behavior. A device may receive audio data, determine that the audio data is indicative of consumption of a product by a user. The device may determine, based on the product, a measureable attribute associated with the user. The device may receive first data associated with the measureable attribute. The device may determine that the first data exceeds a threshold. The device may generate a message for presentation.

Abstract: Disclosed herein are methods for selecting one or more tumor-specific neoantigens from a tumor of a subject for a personalized immunogenic composition. Also disclosed herein are methods for treating cancer in a subject in need thereof by administering an immunogenic composition comprising tumor-specific neoantigens selected using the methods disclosed herein.

Abstract: Provided herein are immunogenic compositions comprising tumor-specific neoantigen long peptides, tumor-specific neoantigen short peptides, and adjuvant, optionally a helper peptide, and optionally a tumor-specific peptide. The disclosure also provides methods of using these immunogenic compositions for treating cancer.

Abstract: Disclosed herein are methods for ranking tumor-specific neoantigens from a tumor of a subject that are suitable for subject-specific immunogenic compositions. Suitable tumor-specific neoantigens are tumor-specific neoantigens that are likely presented on the cell surface of the tumor, are likely to be immunogenic, are predicted to be expressed in sufficient amounts to elicit an immune response in the subject, optionally represent sufficient diversity across the tumor, and have relatively high manufacture feasibility. The present methods take a set of neoantigens (peptide vaccine candidates) and ranks the neoantigens in a way such that a group of top-ranked neoantigens simultaneously promotes cell-surface presentation of important neoantigens for Class I and Class II MHC molecules. The top-ranked neoantigens can then be further narrowed according manufacturability and/or other criteria.

Abstract: Techniques for generating multiple-resolutions of time series data are described. An input irregular time series having a plurality of data points is obtained, each data point of the plurality of data points including a timestamp and a feature vector. Based on the input irregular time series, multiple variant time series are generated. A data point in one of the variant time series is based in part on a combination of at least two data points of the input irregular time series. The multiple variant time series can then be used for machine learning tasks such as training a machine learning model or using a machine learning model to infer an output.

Abstract: A thermoplastic polyurethane resin composition comprising: a thermoplastic polyurethane resin; an ultraviolet absorber package comprising a benzotriazole compound (UVA1), and a triazine compound (UVA2) wherein the mass ratio of UVA1 to UVA2 is from 1:1 to 3:1; optionally, a hindered amine light stabilizer and/or an antioxidant compound; and wherein the thermoplastic polyurethane resin composition has a maximum ultraviolet transmittance of ?3% in the wavelengths between 280 nm and 365 nm and an ultraviolet transmittance of ?6% in the wavelengths between 365 nm and 370 nm when the thermoplastic polyurethane resin is formed into a film having a thickness of 6 mils and wherein the cumulative weight % of UVA1 and UVA2 in the polyurethane resin composition ranges from 0.5 wt % to 0.85 wt % based on the total weight of the polyurethane resin composition.

Abstract: Techniques are described and relate to assigning peptides to peptide groups for vaccine development. In an example, a peptide property of a peptide is determined, where this peptide is from different peptides that are to be assigned to different groups of vaccine. A determination is also made that the peptide is to be assigned to a first group from the different groups based at least in part on the peptide property. The first group has a first group property that is based at least in part on peptide properties of first peptides to be assigned to the first group. The first group property is within a similarity range relative to a second group property of a second group from the different groups. Information is generated and indicates that the peptide is assigned to the first group.

Abstract: Comparisons between two nucleotide sequences can be performed by customized integrated circuitry that can implement a Smith Waterman analysis in series, as opposed to the parallel implementations known in the art. Series performance enables such customized integrated circuitry to take advantage of optimizations, including enveloping thresholds that demarcate between cells of a two-dimensional matrix for which nucleotide comparisons are to be performed, and cells of the two-dimensional matrix for which no such comparison need be performed, and, instead, a value of zero can simply be entered. Additionally, such customized integrated circuitry facilitates the combination of multiple control units, each directing the comparison of a unique pair of nucleotides, with a single calculation engine that can generate values for individual cells of the two-dimensional matrices by which such pairs of nucleotides are compared.

Abstract: Described are methods and systems for identifying phenotypic traits of an individual from nucleotide sequence data. The methods and systems are useful even when the identity of the individual or phenotypic traits of the individual is unknown.

Abstract: Comparisons between two nucleotide sequences can be performed by customized integrated circuitry that can implement a Smith Waterman analysis in a reduced memory footprint, storing and referencing only individual portions, or subsections, of a two-dimensional matrix that is representative of the comparison between the two nucleotide sequences. As the backtracking proceeds, backtracking metadata corresponding to a cell from a subsection that is not currently retained in memory can be required. Such a subsection can be regenerated from previously generated scores associated with checkpoint cells of the two-dimensional matrix that comprise two edges of the subsection being regenerated.

Abstract: Comparisons between two nucleotide sequences can be performed by customized integrated circuitry that can implement a Smith Waterman analysis in series, as opposed to the parallel implementations known in the art. Series performance enables such customized integrated circuitry to take advantage of optimizations, including enveloping thresholds that demarcate between cells of a two-dimensional matrix for which nucleotide comparisons are to be performed, and cells of the two-dimensional matrix for which no such comparison need be performed, and, instead, a value of zero can simply be entered. Additionally, such customized integrated circuitry facilitates the combination of multiple control units, each directing the comparison of a unique pair of nucleotides, with a single calculation engine that can generate values for individual cells of the two-dimensional matrices by which such pairs of nucleotides are compared.

Abstract: Comparisons between two nucleotide sequences can be performed by customized integrated circuity that can implement a Smith Waterman analysis in a reduced memory footprint, storing and referencing only individual portions, or subsections, of a two-dimensional matrix that is representative of the comparison between the two nucleotide sequences. As the backtracking proceeds, backtracking metadata corresponding to a cell from a subsection that is not currently retained in memory can be required. Such a subsection can be regenerated from previously generated scores associated with checkpoint cells of the two-dimensional matrix that comprise two edges of the subsection being regenerated.

Abstract: A machine-implemented method for detecting scareware includes the steps of accessing one or more landing pages to be evaluated, extracting one or more features from the landing pages, and providing a classifier to compare the features extracted from the landing pages with features of known scareware and non-scareware pages. The classifier determines a likelihood that the landing page is scareware. If determined to be scareware, the landing page is removed from search results generated by a search engine. The features can be URLs, text, image interest points, image descriptors, a number of pop-ups generated, IP addresses, hostnames, domain names, text derived from images, images, metadata, identifiers of executables, and combinations thereof.

Abstract: A machine-implemented method for detecting scareware includes the steps of accessing one or more landing pages to be evaluated, extracting one or more features from the landing pages, and providing a classifier to compare the features extracted from the landing pages with features of known scareware and non-scareware pages. The classifier determines a likelihood that the landing page is scareware. If determined to be scareware, the landing page is removed from search results generated by a search engine. The features can be URLs, text, image interest points, image descriptors, a number of pop-ups generated, IP addresses, hostnames, domain names, text derived from images, images, metadata, identifiers of executables, and combinations thereof.

Abstract: A particular method of content personalization based on user information includes receiving data representing an information retrieval task. The data is received at a server from a computing device associated with a user. The information retrieval task is executed to generate result information. Personalization information associated with the user that is relevant to the information retrieval task is retrieved. The personalization information associated with the user includes information associated with at least one of a genotype of the user and a phenotype of the user. The method includes modifying the result information based on the retrieved personalization information to generate personalized result information.

Abstract: The system and method of the present invention automatically assigns “scores” to the predictor/variable value pairs of a conventional probabilistic model to measure the relative impact or influence of particular elements of a set of topics, items, products, etc. in making specific predictions using the probabilistic model. In particular, these scores measure the relative impact, either positive or negative, that the value of each individual predictor variable has on the posterior distribution of the target topic, item, product, etc., for which a probability is being determined. These scores are useful for understanding why each prediction is made, and how much impact each predictor has on the prediction. Consequently, such scores are useful for explaining why a particular prediction or recommendation was made.

Abstract: Cluster models are described herein. By way of example, a system for predicting binding information relating to a binding of a protein and a ligand can include a trained binding model and a prediction component. The trained binding model can include a probability distribution and a hidden variable that represents a cluster of protein sequences, and/or a set of hidden variables representing learned supertypes. The prediction component can be configured to predict the binding information by employing information about the protein's sequence, the ligand's sequence and the trained binding model.

Abstract: The invention relates to a system for filtering messages—the system includes a seed filter having associated therewith a false positive rate and a false negative rate. A new filter is also provided for filtering the messages, the new filter is evaluated according to the false positive rate and the false negative rate of the seed filter, the data used to determine the false positive rate and the false negative rate of the seed filter are utilized to determine a new false positive rate and a new false negative rate of the new filter as a function of threshold. The new filter is employed in lieu of the seed filter if a threshold exists for the new filter such that the new false positive rate and new false negative rate are together considered better than the false positive and the false negative rate of the seed filter.