Abstract: A computer-implemented method for constructing a state transition graph, wherein the method includes obtaining data that includes treatment history and clinical data of a cohort of patients; and generating, by the one or more computing devices, individual treatment pathways for individual patients of the cohort of patients using the treatment history and clinical data for the individual patients; wherein the individual treatment pathways are generated using user-defined parameters including: one or more qualifying events; one or more response states to the one or more qualifying events; and one or more reversible or collapsible events. The method additionally includes constructing a state transition graph that represents multiple aligned and merged individual treatment pathways including the one or more qualifying events, the one or more response states to the one or more qualifying events and the one or more reversible or collapsible events.

Abstract: A method (100, 200, 400) for predicting a response of a tumor to immunotherapy, comprising: analyzing (120) a tumor sample; analyzing (130) a non-tumor sample obtained from the patient; identifying (140) one or more tumor-specific mutations; analyzing (150) the genetic information from the tumor sample to determine a variant allele frequency for the identified tumor-specific mutations; analyzing (160) genetic information to determine a tumor purity of the patients tumor; determining (210) a pathogenicity for the identified tumor-specific mutations; calculating (220), from: (i) the determined variant allele frequency and/or a determined allele-specific expression, exon expression, or gene expression of the one or more tumor-specific mutations; (ii) the determined tumor purity; and (iii) the determined pathogenicity, a tumor functional mutation load score; predicting (410), based on the score, a response of the patients tumor to an immunotherapy treatment; and determining (420), based on said prediction, a trea

Abstract: A method (100) comprising: (i) providing (104, 106) a reference data set for a first gene expression platform and a training data set for a second platform; (iii) computing (108) a boundary expression level that distinguishes between the subtypes; (iv) generating (1 10) a confusion matrix; (v) determining (112) an effectiveness of the gene markers to discriminate between the subtypes; (vi) filtering (114) any gene marker with an expression level below a threshold or with determined effectiveness below a threshold; (v) calculating (118) a mean and/or median expression level for each subtype, and comparing them to generate an expression level change; (vi) comparing (118) the expression level change to a reference expression level change; and (vii) selecting (120) the gene marker if the generated expression level change and the reference expression level change are changed in the same direction; and (viii) providing (124) the selected gene markers via a user interface.

Abstract: A method (100) for characterizing gene transcript expression levels, comprising: (i) extracting (110) one or more unique features from each of a plurality of gene transcripts; (ii) storing (120) the extracted unique features in a unique feature database; (iii) receiving (130) a plurality of sequences sequenced from gene transcripts, wherein at least some of the sequences comprise one or more of the extracted unique features; (iv) comparing (140), by a processor, the plurality of sequences to the extracted unique features stored in the unique feature database; (v) identifying (150), based on a match between a sequence and an extracted unique feature, a gene transcript and/or gene from which the sequence was generated; and (vi) compiling (160) information about gene transcript expression levels based on said identified gene transcripts.

Abstract: A system and method for providing sequencing of biomolecules, which can be used for differential analysis of a test sample from a normal sample.

Abstract: A method for evaluating nucleic acid sequencing data using a quality control analysis system, comprising: receiving a plurality of reads of a nucleic acid sequence; extracting a plurality of k-mers from the plurality of reads; identifying, using the plurality of extracted k-mers, one or more of a plurality of annotated k-mers found in the plurality of reads, wherein the plurality of extracted k-mers are stored in an annotation database, and further wherein the annotated k-mers are annotated with annotation information about the one or more nucleic acid sequences from which the annotated k-mers are generated; gathering, based on the identified annotated k-mers found in the plurality of reads, annotation information about the plurality of reads; and determining, based on the gathered annotation information, a quality control metric for at least some of the plurality of reads.

Abstract: In patient cohort identification, clustering (30) of patients is performed using a patient comparison metric dependent on a set of features (24). Information is displayed on sample patients who are similar or dissimilar to a query patient according to the clustering. User inputted comparison values are received comparing the sample patients with the query patient. The set of features and/or feature weights are adjusted to generate an adjusted patient comparison metric having improved agreement with the user inputted comparison values. The clustering is repeated using the adjusted patient comparison metric. A patient cohort is identified from a cluster (34) containing the query patient produced by the last clustering repetition. The information on the sample patients may be shown by simultaneously displaying two or more graphical modality representations (70, 72, 74) each plotting the sample patients and the query patient against two or more features of the modality.

Abstract: A system for characterizing intercellular communication and heterogeneity in cancer tumors, and more particularly a method for detecting sub-populations and receptor-ligand states for providing predictive information in relation to cancer and cancer treatment is disclosed. The system comprises the steps of obtaining from a NGS sequencer, single-cell RNA-seq for a plurality of cells within a tumor, correlation with a plurality of data sets from a curated gene list of receptor-ligand pairs, normalizing their transcript abundance data, assigning states (e.g. 0,1,2,3) to each curated receptor-ligand pair in each cell (e.g.

Abstract: A data-driven integrative visualization system and a method for visualization and exploration of the multi-modal features of a cohort of samples, is disclosed Specifically, a method for providing an interactive computation and visualization front-end of a genomics platform for presenting the complex multiparametric and high dimensional, multi-omic data of a patient with respect to a cohort of samples, that assists the user in understanding the similarities and differences across individual or groups of samples, identify correlation among different features and improve treatment planning and long term patient care, is described. The method may include obtaining and inputting multi-omic data of a patient and/or cohorts, identifying multi-modal feature variations and their relationships, and displaying this information in an interactive circular format on a GUI, from which the user can access further information.

Abstract: A data-driven integrative visualization system and method for summarizing and presenting genomic aberrations, their drug responses and multi-omic data of a patient, is disclosed. Specifically, a method for displaying genomic aberrations and multi-omic data of a patient in an interactive tool which allows the medical practitioner to access underlying supporting biologic and scientific evidence from relevant knowledge bases through a set of graphical interactions, is described. The method comprises the steps of obtaining and inputting multi-omic data of a patient or cohorts, identifying genomic aberrations and their drug responses, and displaying this information in a first level interactive classical/circular ideogram in one or multiple layers on a GUI, from which the user can access and view further information on the gene and molecular levels. The system provides an improved process of integrative analysis on a patient's multi-omic data for effective treatment planning.

Abstract: A method of identifying co-expressed coding and noncoding genes is disclosed. The method may include receiving genetic sequences, mapping the genetic sequences to known coding and noncoding genes, correlating the mapped genes, and generating a co-expression network. A system for generating a co-expression network and providing the co-expression network to a user on a display is disclosed. The system may include a memory, one or more processors, one or more databases, and a display.

Abstract: Data-driven generalized regression-based frameworks that support the transformation of measurements, applicable but not limited to gene expressions, from one platform to another over a wide dynamic range, with selected summary statistics/feature values as predictors for the model parameters. The framework consists of primary model training and transformation, and additional levels of categorical regression and transformation processes.

Abstract: Advertisements or other types of targeted information are delivered to set-top boxes or other user interface devices of a signal distribution system. In one aspect of the invention, at least one multicast update comprising updated targeted information is sent to the user interface devices during a multicast update period. If a given one of the user interface devices is unable to obtain a complete set of the updated targeted information from the multicast update before timeout of the multicast update period, a unicast update comprising at least a portion of the updated targeted information is sent to the given user interface device during a unicast update period. The unicast update may be sent responsive to a request from the given user interface device for a designated portion of the updated targeted information.

Abstract: Systems and methods facilitate the location and/or identification of repetitive DNA patterns, such as CpG islands, Alu repeats, tandem repeats and various types of satellite repeats. These repetitive elements can be found within a chromosome, within a genome or across genomes of various species. The systems and methods apply image processing operators to find prominent features in the vertical and horizontal direction of the DNA spectrograms. The systems and methods for detecting and/or classifying repetitive DNA patterns include: (a) a comparative histogram method, (b) feature selection and classification using support vector machines and genetic algorithms, and (c) generation of a spectrovideo from a plurality of spectral images.

Abstract: Advertisements or other types of targeted information are delivered to set-top boxes or other user interface devices of a signal distribution system. In one aspect of the invention, at least one multicast update comprising updated targeted information is sent to the user interface devices during a multicast update period. If a given one of the user interface devices is unable to obtain a complete set of the updated targeted information from the multicast update before timeout of the multicast update period, a unicast update comprising at least a portion of the updated targeted information is sent to the given user interface device during a unicast update period. The unicast update may be sent responsive to a request from the given user interface device for a designated portion of the updated targeted information.

Abstract: Spectrogram extraction from DNA sequence has been known since 2001. A DNA spectrogram is generated by applying Fourier transform to convert a symbolic DNA sequence consisting of letters A, T, C, G into a visual representation that highlights periodicities of co-occurrence of DNA patterns. Given a DNA sequence or whole genomes, with this method it is easy to generate a large number of spectrogram images. However, the difficult part is to elucidate where are the repetitive patterns and to associate a biological and clinical meaning to them. The present disclosure provides systems and methods that facilitate the location and/or identification of repetitive DNA patterns, such as CpG islands, Alu repeats, tandem repeats and various types of satellite repeats. These repetitive elements can be found within a chromosome, within a genome or across genomes of various species.