Abstract: Systems and methods include a computer-implemented method for random selection and use of observation cells. Observation cells are randomly selected from a model of process-based reactive transport modeling (RTM). The observation cells are incorporated into a neural network for proxy modeling. A set of parameter-specific proxy models represented by a neural network is trained. Each parameter-specific proxy model corresponds to a specific RTM parameter from a set of RTM parameters. Blind tests are performed using the set of parameter-specific proxy models, where each blind test tests a specific one of the parameter-specific proxy models. Predictions are generated using the set of parameter-specific proxy models. 3-dimensional interpolation the observation cells is performed.

Abstract: In accordance with embodiments, a computing device of a processing system performs a seed search of a short read (SR) against a reference sequence using a Burrows Wheeler Transform (BWT) algorithm to determine a seed. During the seed search one or more seed candidates in the reference sequence are determined. If the number of matches is less than or equal to a predefined threshold value the seed search using the BWT algorithm is stopped. Each seed candidate is extended to a respective extended seed candidate equal in length to the SR. bp-to-bp comparisons are performed between a remaining bp sequence of the SR after the matching bp and a corresponding remaining bp sequence in each extended seed candidate. An extended seed candidate that exactly matches the SR in the bp-to-bp comparisons is outputted as the seed.

Abstract: Techniques for predicting a protein sequence are described. An exemplary method includes receiving a request to predict a missing area of a protein's primary sequence and a corresponding three-dimensional position of the missing area; applying a machine learning model to backbone Cartesian coordinates of the protein's primary sequence and a protein vector of a representation of the protein's primary sequence including the missing area to predict a missing area of the protein primary sequence and a corresponding three-dimensional position for the missing area, wherein the machine learning model is selected from the group consisting of: an attention-based machine learning model, a bidirectional long short term memory-based model, and a convolutional neural network-based model; and outputting a result of the machine learning model.

Abstract: In comparison to conventional sequencing pileup algorithms, the process described herein generates sequencing pileups that contains additional information not typically reported by conventional algorithms while also consuming fewer computational resources (e.g., time, processing power, and memory). First, each of a FASTA reference genome and BAM sequence read files are converted to an internal representation. This enables the rapid iteration across nucleotide bases of the sequence reads to determine support characteristics that summarize information of nucleic acid molecules corresponding to positions across the reference genome. Next, the support characteristics of positions across the reference genome are stored through a memory allocation process that utilizes a first and a second temporary storage. This enables the convenient freeing of one temporary storage while the other temporary storage is being used.

Abstract: A method includes receiving electroencephalographic (EEG) signal data recordings collected from a plurality of individuals via at least one EEG monitoring device. An optimized plurality of wavelet packet atoms is constructed based on the EEG signal data recordings and a mother wavelet. The optimized plurality of wavelet packet atoms is reordered to obtain an optimal reordered set of wavelet packet atoms. The optimal reordered set of wavelet packet atoms is normalized to obtain an optimal normalized set of wavelet packet atoms that is representative of brain activities of the plurality of individuals. A particular EEG signal data recording of a particular individual is received, which is projected onto the optimal normalized set of wavelet packet atoms to obtain an individual-specific set of projections for the particular individual on the optimal normalized set of wavelet packet atoms.

Abstract: Methods and systems for processing a plurality of sample reads for genome sequencing include, for each sample read of the plurality of sample reads, comparing substring sequences from the sample read to reference sequences representing different portions of a reference genome. One or more reference sequences are identified that match one or more of the compared substring sequences, and a probabilistic location within the reference genome is determined for the sample read based on the one or more identified reference sequences. The reference genome is partitioned for reference-aligned genome sequencing based on the determined probabilistic locations of the respective sample reads.

Abstract: The present invention provides a powerful tool to identify personalized therapeutic strategies. In particular, the invention provides methods for determining therapeutically targetable dominant signaling pathways in a cancer sample from a subject affected with a solid cancer, determining a treatment protocol for the subject, selecting a subject for a therapy, determining whether the subject is susceptible to benefit from a therapy, predicting clinical outcome of the subject, treating the subject and/or predicting the sensitivity of a solid cancer to a therapy.

Abstract: Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.

Abstract: Method and apparatus for the coding and selective access of compressed genomic sequence data produced by genomic sequencing machines. The coding process is based on aligning sequence reads with respect to pre-existing or constructed reference sequences, on classifying and coding the sequence reads by means of sets of descriptors, and further partitioning the descriptor sets into access units of different types. Efficient selective access to specific genomic regions with the guarantee of retrieving all sequence reads mapped to those regions, is provided by: signaling the type of data mapping configuration used to store or transmit the descriptor sets, determining the minimum number of access units that need to be retrieved and decoded to access a genomic region, providing a master index table that contain all information for optimizing the data access process.

Abstract: Systems and methods providing a clotting factor VIII dosing regimen are disclosed. The systems and methods include determining an estimated pharmacokinetic profile of a patient using a Bayesian model of pharmacokinetic profiles of sampled patients. The systems and methods can determine a first dosing regimen for a first dosing interval including (i) a first dosage and (ii) a first therapeutic plasma protein level in the patient varying over time based at least upon the estimated pharmacokinetic profile. The systems and methods can determine a second dosing regimen for a second dosing interval including (i) a second dosage and (ii) a second therapeutic plasma protein level in the patient varying over time. The estimated pharmacokinetic profile can be adjusted based on previous patient treatments. Further, a user can select which days a dosage is to be applied such that the protein level does not fall below a target trough.

Abstract: Disclosed are systems, devices, and methods for planning a procedure for treatment of tissue in a patient's lungs. An exemplary method includes generating a three-dimensional (3D) model of the patient's lungs, displaying the 3D model of the patient's lungs, selecting a target location in the tissue of the patient's lungs as displayed on the 3D model, identifying a point on a pleural surface of the patient's lungs with access to the target location, determining an access path between the target location and the identified point on the pleural surface, calculating a risk of injury to intervening structures between the identified point on the pleural surface and the target location, based on the determined access path, and displaying the access path and the calculated risk of injury for the access path on the 3D model.

Abstract: A system and method for predicting gut health of an individual using non-invasive technique has been provided. The system is making use of two types of pathways i.e. one which are beneficial to gut health and the second which are harmful to gut health. These two types of pathways are annotated in the genomes of gut bacteria. Best combinations of subsets of these pathways capable of distinguishing between gut commensals and pathogens are assigned as pathway biomarkers. The identified pathway biomarkers are then used to develop scheme for prediction of gut health status.

Abstract: A method of administering insulin includes receiving subcutaneous information for a patient at a computing device and executing a subcutaneous outpatient program for determining recommended insulin dosages. The subcutaneous outpatient program includes obtaining blood glucose data of the patient from a glucometer in communication with the computing device, aggregating blood glucose measurements to determine a representative aggregate blood glucose measurement associated with at least one scheduled blood glucose time interval, and determining a next recommended insulin dosage for the patient based on the representative aggregate blood glucose measurement and the subcutaneous information. The method also includes transmitting the next recommended insulin dosage to a portable device associated with the patient. The portable device displays the next recommended insulin dosage.

Abstract: In certain embodiments, the invention stems from the discovery that analysis of population distribution curves of metabolite levels in blood can be used to facilitate predicting risk of autism spectrum disorder (ASD) and/or to differentiate between ASD and non-ASD developmental delay (DD) in a subject. In certain aspects, information from assessment of the presence, absence, and/or direction (upper or lower) of a tail effect in a metabolite distribution curve is utilized to predict risk of ASD and/or to differentiate between ASD and DD.

Abstract: A method for nucleic acid sequencing includes receiving observed or measured nucleic acid sequencing data from a sequencing instrument that receives and processes a sample nucleic acid in a termination sequencing-by-synthesis process. The method also includes generating a set of candidate sequences of bases for the observed or measured nucleic acid sequencing data by determining a predicted signal for candidate sequences using a simulation framework. The simulation framework incorporates an estimated carry forward rate (CFR), an estimated incomplete extension rate (IER), an estimated droop rate (DR), an estimated reactivated molecules rate (RMR), and an estimated termination failure rate (TFR), the RMR being greater than or equal to zero and the TFR being lesser than one. The method also includes identifying, from the set of candidate sequences of bases, one candidate sequence leading to optimization of a solver function as corresponding to the sequence for the sample nucleic acid.

Abstract: A method for time constant estimation includes generating a bound for a R=1/g of the inverse solution; for any R picked within the bound for R, extracting the voltage dependence of the time constant; and extracting the roots of a tree like structure. A method to quantify a time constant of each gate of a Hodgkin Huxley formalism with activating and inactivating gates with currents recorded with a T-step and G-step protocols, and methods to quantify a time constant of each gate of a Hodgkin Huxley formalism with activating and inactivating gates are also described.

Abstract: Metallic alloy development has been traditionally based on experimental or theoretical equilibrium phase diagrams and the like. The synthesis, processing and mechanical testing of small and large real samples are a challenging task requiring huge amount of effort in terms of time, money, resource, tedious testing and processing equipment and man-hour for which conventional Calphad calculations etc. alone do not help much in their local structure and related property prediction. Embodiments of the present disclosure provide simulation systems and methods for structure evolution and property prediction Molecular Dynamics (MD) combined with accelerated Monte Carlo techniques, wherein information on atomic elements and composition specific to alloy material is obtained to generate a MD potential file that is further used to generate a 3D structure file by executing a structure equilibration technique.

Abstract: A distributed network system and method includes a processing unit configured to manage safety data for a plurality of medical devices, a database software component in communication with the processing unit, and a monitoring software component in communication with the processing unit. The monitoring software component is configured to monitor a number of messages between a number of medical devices and the processing unit, to process performance parameters to generate an overall performance index, and to generate an output that is viewable by a user. The output includes relative contributions of each of the performance parameters to the overall performance index, where the overall performance index is generated using a weighting factor associated with each of the performance parameters. The performance parameters include the number of messages waiting to be processed, which has the largest weighting factor, and a disk queue length, which has the smallest weighting factor.

Abstract: An infant formula for preventing gastro-esophageal reflux is disclosed comprising whey protein and/or casein, a galactomannan thickener, and a fermented milk-derived product.

Abstract: A method for the deconvolution of nucleic acid-containing substance mixtures using synthetically generated target nucleotide sequences. Starting from a plurality of nucleotides,, a plurality of different target nucleotide sequences (TNS) is generated according to a predetermined algorithm. At least one of the TNS generated is associated with at least one substance or substance combination and chemically coupled thereto. At least one substance mixture to be analysed and having at least two different TNS is provided and is sequenced according to a sequencing method., at the same time all TNS contained in the substance mixture are detected in a common sequence spectrum. To facilitate the deconvolution, the sequence spectra of a substance mixture should be deducted/subtracted from each other prior to and after a selection experiment.