Abstract: A data processing system configured for computer visualization of drugs for drug interaction information retrieval is disclosed. For each of multiple different substances and using a camera within the mobile or other computing device, imagery of at least one external characteristic of a physical body of the substance is acquired. An identity of each of the multiple different substances is determined based upon the at least one external characteristic from the acquired imagery. Drug interaction data is retrieved for each of the multiple different substances using the determined identities. Drug interaction data for at least one of the multiple different substances is correlated with at least one other of the multiple different substances. At least one generic substance and/or cost information of at least one of the multiple different substances is identified. The correlated drug interaction data, the at least one generic substance, and/or the cost information are displayed.

Abstract: Phasing unphased genotype data of an individual includes: obtaining the unphased genotype data of the individual; processing the unphased genotype data to determine phased haplotype data, the processing comprising performing out-of-sample population-based phasing on the unphased genotype data; wherein: performing out-of-sample population-based phasing includes performing statistical analysis using predetermined reference data that is based on genotype data of a reference population; and the genotype data of the reference population does not reference the genotype data of the individual.

Abstract: Computer software products, methods, and systems are described which provide functionality to a user conducting experiments designed to detect and/or identify genetic sequences and other characteristics of a genetic sample, such as, for instance, gene copy number and aberrations thereof. The presently described software allows the user to interact with a graphical user interface which depicts the genetic information obtained from the experiment. The presently disclosed methods and software are related to bioinformatics and biological data analysis. Specifically, provided are methods, computer software products and systems for analyzing and visually depicting genotyping data on a screen or other visual projection. The presently disclosed methods and software allow the user conducting the experiment to differentially filter complex genetic data and information by varying genetic parameters and removing or highlighting visually various regions of genetic data of interest (CytoRegions).

Abstract: A system and method for converting static/still medical images of a particular patient into dynamic and interactive images interacting with medical tools including medical devices by coupling a model of tissue dynamics and tool characteristics to the patient specific imagery for simulating a medical procedure in an accurate and dynamic manner by coupling a model of tissue dynamics to patient specific imagery for simulating cerebral aneurysm clipping surgery.

Abstract: A method and apparatus providing a haptic monitor system capable of generating haptic cues based on sensed information are disclosed. The haptic system includes a sensing device, a digital processing unit, and a haptic generator. The sensing device is configured to selectively sense an individual's or user vital information via one or more wearable sensors, and subsequently forwards the sensed vital information to the digital processing unit for data processing. Upon receipt of the vital information, the digital processing unit provides a haptic signal in response to the vital information. The haptic generator, subsequently, generates haptic feedback in accordance with the haptic signal.

Abstract: A wearable electronic device, comprising a heart rate sensor to determine a heart rate of the user, a motion sensor to detect motion of a user, the motion sensor operated in an initial calibration phase during which the heart rate sensor is detecting the heart rate of the user, and the motion sensor is detecting the motion of the user, the calibration phase being used to compute a correspondence between motion of the user and the heart rate of the user, the motion sensor being operated in a low power phase during which the heart rate sensor is powered down, and a processor configured to run a heart rate estimation module configured to calculate an estimated heart rate of the user based upon the motion of the user and the correspondence between the heart rate of the user and the motion of the user determined in the calibration phase.

Abstract: The redundancy in genomic sequence data is exploited by compressing sequence data in such a way as to allow direct computation on the compressed data using methods that are referred to herein as “compressive” algorithms. This approach reduces the task of computing on many similar genomes to only slightly more than that of operating on just one. In this approach, the redundancy among genomes is translated into computational acceleration by storing genomes in a compressed format that respects the structure of similarities and differences important to analysis. Specifically, these differences are the nucleotide substitutions, insertions, deletions, and rearrangements introduced by evolution. Once such a compressed library has been created, analysis is performed on it in time proportional to its compressed size, rather than having to reconstruct the full data set every time one wishes to query it.

Abstract: In general, one aspect of the subject matter described in this specification is embodied in operations of processing sequence data by selecting a distribution key according to a type of one or more tasks to be performed on the data. The key is one or more data fields of a sequence data file, e.g., a sequence alignment/map (SAM) format or binary sequence alignment/map (BAM) format file, or derived from one or more data fields of a sequence data file. The sequence data is then distributed to multiple nodes of a parallel processing relational database system. The system performs the tasks of processing the sequence data by executing database queries. The system executes the database queries on multiple nodes in parallel. The system can use query optimization functions built into the database to expedite performance of each task.

Abstract: The present disclosure provides systems and methods for nucleic acid sequence analysis. A system for processing raw nucleic acid sequence data from a genomic sequencer comprises a data processing server having a housing contained therein one or more processing modules. The one or more processing modules can each comprise an electronic control unit programmed to align nucleic acid sequence data from a genomic sequencing device and perform one or more of variant analysis and structural variant analysis on the nucleic acid sequence data. The system can further comprise a computer server in communication with the processing server. The computer server can be programmed or otherwise configured to process and/or analyze the aligned nucleic acid sequence data.

Abstract: A system and method for performing similarity searching is disclosed wherein programmable logic devices such as field programmable gate arrays (FPGAs) can be used to implement Bloom filters for identifying possible matches between a query and data. The Bloom filters can be implemented in a parallel architecture where the different parallel Bloom filters share access to the same memory units.

Abstract: A computer system is provided for determining the relative effectiveness of anti-cancer drugs. The interface has selectable options, including an option to manage drug testing parameters, and enables user selection of desired drug testing parameters in relation to a virtual well plate associated with a physical well plate of a spectrophotometer. The computer system causes the spectrophotometer to start a drug test, wherein the physical well plate includes at least one test well containing viable cancer cells; and at least one drug candidate in a predetermined concentration; and at least one control well containing the viable cancer cells alone. The system records the optical density of the well at a predetermined wavelength at selected time intervals for a selected duration of time, and stores the optical density and time measurements in the database.

Abstract: This disclosure relates to methods for identifying an antibody, a target molecule, or an agent by analyzing the immunoglobulin repertoire sequence data in a sample and by determining the most dominant VH and VL chains present in said sample, as well as materials used therewith.

Abstract: According to embodiments, techniques for selecting a consistent part of a signal, including a photoplethysmograph (PPG) signal, are disclosed. A pulse oximetry system including a sensor or probe may be used to obtain a PPG signal from a subject. Signal peaks may be identified in the PPG signal. Characteristics of the signal peaks, including the amplitude levels of the signal peaks and/or the time-distance between the signal peaks may be used to determine if the PPG signal is consistent. In an embodiment, signal peaks are processed based on a consistency metric, and the processed signal peaks are compared to the consistency metric to determine if the PPG signal is consistent. If the PPG signal is determined to be consistent, the PPG signal may be further analyzed to determine an underlying signal parameter, including, for example, a patient respiration rate.

Abstract: Described embodiments enable identification of family networks using combinations of DNA analysis and genealogical information. Genealogical data is provided by users of a genealogical research service or collected from other sources and used to create family trees for each user. DNA samples are also received from the users. By analyzing the DNA samples, potential genetic relationships can be identified between some users. Once these DNA-suggested relationships have been identified, common ancestors can be sought in the respective trees of the potentially related users. Where these common ancestors exist, an inference is drawn that the DNA-suggested relationship accurately represents a familial overlap between the individuals in question. People descended from the same common ancestor are each members of a family network. Members of a family network not in a user's tree may be identified for the user, enabling the user to discover additional ancestors that might otherwise have remained unknown.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may generate a lag matrix, which includes multiple segments of the physiological signal each having the same number of values. The system may generate a correlation matrix, which includes multiple correlation values, based on the lag matrix. The system may identify a peak in the correlation lag matrix, or a processed matrix derived thereof, and the corresponding lag value. The correlation matrix, or processed matrix thereof, may be rotated, averaged, or otherwise transformed by the system to identify the lag value. The system may determine physiological rate information based on the identified lag value.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, and other information, such as signal-to-noise information, from a physiological signal. The system may generate at least one difference signal based on the physiological signal and sort the at least one difference signal to generate at least one sorted difference signal. The system may analyze the at least one sorted difference signal to determine at least two values indicative of noise. The system may determine a value indicative of a signal-to-noise ratio based on the two or more values indicative of noise.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, and other information, such as noise information, from a physiological signal. The system may generate a first difference signal based on a first segment of the physiological signal and sort the first difference signal to generate a first sorted difference signal. The system may generate a second difference signal based on a second segment of the physiological signal and sort the second difference signal to generate a second sorted difference signal. The first and second sorted difference signals may be analyzed and a value indicative of noise may be determined based on the analysis.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a period associated with a physiological rate. The system may generated a first sorted difference signal based on a segment of the physiological signal having a size corresponding to the period. The system may generate second and third sorted difference signals based on segments of the physiological signal having sizes corresponding to a fraction of the period and a multiple of the period. The system may analyze the first, second, and third sorted difference signals, and qualify or disqualify the calculated value based on the analysis.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a period associated with a physiological rate. The system may determine a first value indicative of a baseline of the physiological signal and a second value indicative of a deviation of the physiological signal from the baseline. The first value may, for example, be a median value, an average, or a coefficient corresponding to a best fit curve of the physiological signal. The second value may be a standard deviation value, a standard error, or a root mean square value based on the physiological signal. The system may qualify or disqualify the calculated value based on the first and second values.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may determine a skew metric based on the physiological signal. The system may determine an algorithm setting based on a reference relationship between the determined skew metric and a value indicative of a physiological rate. The algorithm setting may, for example, affect the amount of filtering applied to the physiological signal.