Abstract: A genomic/proteomic test synthesis method includes receiving a genomic/proteomic data set (12) comprising samples corresponding to persons with each sample including values of features of a set of features derived from genomic/proteomic data for the corresponding person. For each feature, univariate analysis (30) is performed to generate a sample density versus feature value data set for the feature, for example represented as a kernel density estimate (KDE) (52). Multivariate analysis (32, 34) is performed on the features using the KDEs to generate a set of discriminative features (36, 38). In one example, the multivariate analysis (32) uses energy spectral density (ESD) characteristics of the KDEs. In another example, the multivariate analysis (34) uses peak location characteristics of the KDEs.

Abstract: Methods, systems and apparatus for detecting patterns in constituents of at least one biological organism are disclosed. In accordance with one method, clusters of the constituents are determined (208) by selecting (210) different subsets of at least one of genes or proteins and identifying (212) the clusters from biological data corresponding to the selected subsets. Here, membership values for the constituents, indicating membership within the clusters, are calculated for use as a basis of an additional cluster determination process (208) to obtain final clusters of constituents. By underpinning the preliminary clustering on different subsets of biological data and formulating the higher-level clustering on the basis of the membership values, the embodiments can enable an evaluation of a large variety of biological data in a practical, accurate and highly efficient manner.

Abstract: The present disclosure describes systems and methods for generating a priority score for a variant of a gene based on its potential significance to a disease. Priority scores may be calculated for multiple variants, and the variants may be ranked based on the generated priority scores.

Abstract: A method (100) for recruiting a patient for a clinical trial, comprising: receiving (110) a dataset comprising information about one or more clinical trials each including patient eligibility criteria; extracting (120) the patient eligibility criteria from each of the clinical trials; converting (130) the patient eligibility criteria to a standardized patient eligibility criterion using a structured clinical trial mark-up language; storing (140) the patient eligibility criterion in a database (862), each of the criterion associated with one or more clinical trials; receiving (150) patient-specific data values about a patient; querying (160) the clinical trial eligibility criteria database using the patient-specific data values to identify eligibility criterion satisfied by the patient-specific data value; identifying (170) a clinical trial associated with the one or more standardized patient eligibility criterion satisfied by a received patient-specific data value; and providing (180) a report of the identifi

Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.

Abstract: A system to identify genes that confer antibiotic resistance, comprising: a processor configured to: (i) identify a set of genes present in a sample of genome sequences sequenced from potentially pathogenic isolates; (ii) generate a genome sequence without the identified set of genes; (iii) generate a gene presence-absence matrix listing the genes present in each of the genome sequences, comprising an identification of each of the plurality of genes and an identification of each of the plurality of genome sequences, and comprising an identification of whether each of the genome sequences is obtained from an organism resistant to at least one antibiotic, and further comprising an identification of either presence or absence of the respective gene within the respective genome sequence; and (iv) identify at least one gene or mutation in the plurality of genome sequences associated with antibiotic resistance; and a user interface configured to provide a report.

Abstract: Methods and systems for identifying causal genetic mechanisms of antibiotic resistance in pathogens. In accordance with at least one embodiment, the system includes a gene resistance module to identify genes present in an antibiotic resistant pathogen, a single nucleotide polymorphism module to identify mutations present in an antibiotic resistant pathogen, and an antibiotic resistance module configured to output the causation of antibiotic resistance based on the identified genes and mutations.

Abstract: A method and a system for interpreting data between two quantitative genomic datasets are described, wherein datasets are associated with the same disease or condition, for example, samples from the same patient obtained on different genomic platforms with varying data acquisition parameters. The data samples in each of the first and second datasets are rank ordered and the relative distances among the data samples are determined. The value ranks and relative distances are then used to correlate to data samples in the first and second quantitative genomic datasets, with the output provided to a user, such as a clinician or a patient.

Abstract: A catalog (34) of molecular marker tests specifies molecular marker tests annotated with clinical applicability annotations. An electronic patient medical record (22) stores genetic sequencing data (20) of a patient. A clinical decision support (CDS) system (30) is configured to track the clinical context of the patient wherein the clinical context includes at least a disease diagnosis and a current patient care stage. A catalog search module (32) is configured to search the catalog of molecular marker tests to identify a molecular marker test having clinical applicability to the patient in the clinical context tracked by the CDS system. The search is automatically triggered by occurrence of a trigger event defined by a set of triggering rules. A testing module (44) is configured to perform a molecular marker test identified by the identification module in silico using the genetic sequencing data of the patient stored in the electronic patient medical record.

Abstract: A system and method for providing a prioritized list of clinical trials that are relevant to a patient suffering from an illness or disease, such as cancer, are disclosed. Specifically, a method for conducting an automated, real time clinical trial search and a prioritization analysis is described. The method comprises the steps of conducting an automated full-text clinical trial search based on structuralization of clinical trial eligibility data and knowledge-based inference, initiating a query from the patient's side, and providing a prioritized list of all accessible clinical trials fulfilling a particular query. The system provides better sensitivity, precision and negative predictive value than the current most known clinical trial matching tool: clinicaltrials.gov.

Abstract: A clinical genomic data processing device includes at least one microprocessor (10) and a non-transitory storage medium (12) storing instructions to implement functions of the device. A user interface (26, 28) receives requests for execution of genomic workflows and to display output generated by the execution of the genomic workflows. A genomic workflow manager manages an asynchronous messaging queue (24) and manages the execution of the genomic workflows. Service providers (20) performs jobs associated with the genomic workflows. The genomic workflow manager communicates with the service providers by messages exchanged via the asynchronous messaging queue to manage the execution of the genomic workflows via jobs performed by the service providers.

Abstract: Methods and apparatus for a secure framework for storing and analyzing genomic data. Embodiments of the present invention apply persistent governance to sensitive information and to the analytics that operate upon it, managing the interaction between the two.

Abstract: In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-? signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-? signaling pathway. Related predictive outcome assessment test development methods are also disclosed.

Abstract: The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said biomedical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10, FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR.

Abstract: Methods, systems and apparatus for detecting subpopulations of constituents of at least one biological organism are disclosed. In accordance with exemplary embodiments, cluster partitions of biological data samples compiled from constituents of at least one biological organism are evaluated (114) by computing inconsistency scores for the partitions based on an inconsistency measure. In addition, for at least one of the plurality of partitions, a non-zero value is allocated to the inconsistency measure of at least one cluster that has only one biological data sample. Further, the subpopulations are identified by selecting the partition of having the minimum inconsistency score as the subpopulations.

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: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.

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.