Abstract: It is possible that an analyzer may be operated such that it may perform tests to identify the presence or absence of a specified condition. Such tests may be performed using behaviors which are specific to the specified condition, and the results of those tests may be presented in a single output.

Abstract: A method of storing information using monomers such as nucleotides is provided including converting a format of information into a plurality of bit sequences of a bit stream with each having a corresponding bit barcode, converting the plurality of bit sequences to a plurality of corresponding oligonucleotide sequences using one bit per base encoding, synthesizing the plurality of corresponding oligonucleotide sequences on a substrate having a plurality of reaction locations, and storing the synthesized plurality of corresponding oligonucleotide sequences.

Abstract: A method of using a sequencing cell includes applying an alternating signal across a nanopore of the sequencing cell. The method further includes acquiring a first set of voltage data during a first portion of a plurality of cycles of the alternating signal. The method further includes determining a shifted set of voltage data from the first set of voltage data, computing difference data values by computing differences between data points of the first set of voltage data and corresponding data points of the shifted set of voltage data, identifying a plurality of noise data points as data points having difference data values that are larger than a first threshold value, and removing the plurality of noise data points from the first set of voltage data.

Abstract: Embodiments of the present technology include a method for testing a blood sample for sepsis. The method may include receiving a blood sample from an individual. The method may also include executing an instruction to analyze the blood sample for sepsis. In addition, the method may include measuring values of a set of characteristics in the blood sample. The set of characteristics being determined prior to measuring the values. The method may further include analyzing the values of the set of characteristics to produce a representation of a suspicion of sepsis. In addition, the method may include displaying the representation. Embodiments also include systems for testing blood sample for sepsis.

Abstract: Technology provided herein relates in part to methods, processes, machines and apparatuses for non-invasive assessment of genomic nucleic acid instability and genomic nucleic acid stability. The method comprises providing a set of genomic portions each coupled to a copy number alteration quantification for a test sample, wherein the genomic portions comprises portions of a reference genome to which sequence reads obtained for nucleic acid from a test sample obtained from the subject have been mapped, and the copy number alteration quantification coupled to each genomic portion has been determined from a quantification of sequence reads mapped to the genomic portion; and determining, by a computing device, presence or absence of genomic instability for the subject according to the copy number alteration quantifications coupled to the genomic portions.

Abstract: Disclosed is a method and a system for receiving a request to generate an anonymized pool dataset, wherein the request comprises overall number of people in the dataset, one or more genetic condition categories, a genetic attribute associated with each category, and a percentage of the number of users associated with each category; querying and receiving from a second server a set of datasets associated with people, wherein each dataset comprises health data associated with a user and a corresponding genetic data; generating a pool dataset from the anonymized set of datasets, wherein the pool dataset corresponds to the received overall number of users in the dataset, genetic condition categories, the genetic attribute associated with each category, and a percentage of the number of people in each category.

Abstract: A method for providing nutritional supplement information for a subject is proposed, including a sequence of steps in given order and repeated at least once after a time span of at least 2 days or one week for adapting the provided nutritional information: A) taking a sample from the subject; B) analyzing said sample to determine the nutritional status; C) based on the results calculation of nutritional supplements to improve the nutritional status; D) providing individualized nutritional supplement information. This sequence involves the prediction of at least one initial characteristics matrix and multiplication of this matrix weighted with factors, with an initial recommendation vector for the calculation of a target profile vector after a given first time interval from the profile vector as determined in step B), and in each following cycle adaptation by adapting at least one of the characteristics matrix and the weighting factors.

Abstract: Systems and methods for diagnosing prostate cancer. Image sets (e.g., MRI collected at one or more b-values) and biological values (e.g., prostate specific antigen (PSA)) have features extracted and integrated to produce a diagnosis of prostate cancer. The image sets are analyzed primarily in three steps: (1) segmentation, (2) feature extraction, smoothing, and normalization, and (3) classification. The biological values are analyzed primarily in two steps: (1) feature extraction and (2) classification. Each analysis results in diagnostic probabilities, which are then combined to pass through an additional classification stage. The end result is a more accurate diagnosis of prostate cancer.

Abstract: An analytics system uses metagenomics to generate predictions indicating performance of biological or physical samples. In an embodiment, a method includes determining sequence data of a soil sample. The method further includes determining a plurality of features of the soil sample using the sequence data. The plurality of features is determined based at least in part on a measure of a first microbe detected in the soil sample and a different measure of a second microbe detected in the soil sample. The method further includes inputting the plurality of features to a model trained using measures of the first microbe and the second microbe detected in a plurality of soil samples. The method further includes generating, by the model using the plurality of features, a prediction of physical attribute of a plant grown in the soil sample.

Abstract: The present invention relates to reagent kits for in vitro measurement of YKL-40 and MASP2 and diagnosis of hepatocarcinoma of a test individual.

Abstract: Techniques for determining one or more characteristics of a biological sample using rankings of gene expression levels in expression data obtained using one or more sequencing platforms is described. The techniques may include obtaining expression data for a biological sample of a subject. The techniques further include ranking genes in a set of genes based on their expression levels in the expression data to obtain a gene ranking and determining using the gene ranking and a statistical model, one or more characteristics of the biological sample.

Abstract: Embodiments of the present technology include a method for testing a blood sample for sepsis. The method may include receiving a blood sample from an individual. The method may also include executing an instruction to analyze the blood sample for sepsis. In addition, the method may include measuring values of a set of characteristics in the blood sample. The set of characteristics being determined prior to measuring the values. The method may further include analyzing the values of the set of characteristics to produce a representation of a suspicion of sepsis. In addition, the method may include displaying the representation. Embodiments also include systems for testing blood sample for sepsis.

Abstract: The present disclosure describes systems and methods for predicting adverse health events of patients. In one embodiment, a system obtains a dataset including a plurality of values for each of a plurality of health measurements. The system can obtain the dataset in real-time or substantially real-time after a patient has taken the plurality of health measurements. The system can also obtain metadata about the dataset. The metadata may include a measure of the patient's adherence or non-adherence to a testing routine. The measure of non-adherence may indicate, for example, the quantity of days in a particular time period that the patient failed to conduct the testing routine. The system can apply an algorithm to the dataset and the metadata to generate a risk score. The risk score may indicate the likelihood that the subject will experience an adverse health event.

Abstract: Computationally-efficient techniques facilitate secure pharmacological collaboration with respect to private drug target interaction (DTI) data. In one embodiment, a method begins by receiving, via a secret sharing protocol, observed DTI data from individual participating entities. A secure computation then is executed against the secretly-shared data to generate a pooled DTI dataset. For increased computational efficiency, at least a part of the computation is executed over dimensionality-reduced data. The resulting pooled DTI dataset is then used to train a neural network model. The model is then used to provide one or more DTI predictions that are then returned to the participating entities (or other interested parties).

Abstract: In general, the presently disclosed technology relates to identification of cancer subtypes. More specifically, the technology relates to methods for determining molecular drivers of cancer and/or progression using a multivariate image data and statistical analysis of in-situ molecular markers and morphological characteristics in the same cells of a biological sample suspected of b cancer. This analysis takes place after a single acquisition that obtains the molecular and anatomic morphology data in parallel. The analysis compares specific morphological and molecular markers to known samples exhibiting particular genetic drivers of the cancer. This method provides statistical information that allows for an increased confidence in the identification of specific molecular drivers of the cancer.

Abstract: In a physiological sensor that estimates a true parameter value by providing a predicted parameter value, multiple measurements are taken to increase the accuracy of the predicted parameter value. The sensor can be reapplied between measurements to decrease the probability of an erroneous prediction caused by sensor misplacement. Some measurements can be discarded before calculating a predicted parameter value. The physiological sensor can have a plurality of modes, with one of the modes corresponding to multiple measurement process.

Abstract: A method for tracking a biological parameter of a patient by processing one or more initially-measured values A(n) that correspond to results of one or more biological analyses of the patient's biological parameter from one or more laboratories, may include receiving data from one or more laboratories that includes at least one initial value A(n) and metadata indicating a corresponding normal range. The data is recorded and each of the initial values A(n) are transformed into a normalized value Anorm(n) through the use of a mathematical model and computer processing. A progression over time of the given biological parameter may be generated and displayed using a method of electronic graphical representation, wherein the normalized values Anorm(n) may be presented in combination with at least one element of data that relates to a common normalized normal range.

Abstract: Methods, systems, and software provide machine learning and artificial intelligence including deep neural networks that enable the creation and operation of unique, AI-driven genomic test results augmentation through variable genetic imputation.

Abstract: Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations.

Abstract: A computer implemented method for predicting an agronomical value and a breeding value of a plant belonging to a population, the method includes the steps of: obtaining at least some genotypic data from a subset of lines from the population, obtaining at least some phenotypic data from a subset of lines from the population, providing a statistical model receiving in input the genotypic data and phenotypic data, using the statistical model to output at least an agronomical value estimated for the plant. More particularly, the statistical model is a mixed model combining fixed effects and random effects.