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.

In one aspect, a method is disclosed for using dialects to generate candidate drug compounds. The dialects describe sequences of the candidate drug compounds and activities associated with the sequences. The method includes receiving a data set, training, using the data set, first layers of a machine learning model to determine relationships of components of a portion of a string described by a first dialect. The components pertain to amino acids associated with first activity level information of the sequences. The method includes training, using the data set and the portion of the string, a final layer to generate a remainder of the string. The remainder pertains to second activity level information of the sequences. The method includes generating, using the first and final layer, the string comprising the portion and the remainder. The string represents a candidate drug compound.

The invention relates to a method for a more appropriate thromboembolic event risk assessment based on the presence of different genetic variant. The invention also relates to a method for determining the risk of suffering a thromboembolism disease by combining the absence or presence of one or more polymorphic markers in a sample from the subject with conventional risk factors for thromboembolism as well as computer-implemented means for carrying out said method.

The invention relates to a method for a more appropriate thromboembolic event risk assessment based on the presence of different genetic variant. The invention also relates to a method for determining the risk of suffering a thromboembolism disease by combining the absence or presence of one or more polymorphic markers in a sample from the subject with conventional risk factors for thromboembolism as well as computer-implemented means for carrying out said method.

The invention relates to an in silico screening method to identify candidate excipients for reducing aggregation of a protein in a formulation. The method combines computational molecular modeling and molecular dynamics simulations to identify sites on a protein where non-specific self-interaction and interaction of different test excipients may occur, determine the relative binding energies of such interactions, and select one or more test excipients that meet specified interaction criteria for use as candidate excipients in empirical screening studies.

The invention relates to an in silico screening method to identify candidate excipients for reducing aggregation of a protein in a formulation. The method combines computational molecular modeling and molecular dynamics simulations to identify sites on a protein where non-specific self-interaction and interaction of different test excipients may occur, determine the relative binding energies of such interactions, and select one or more test excipients that meet specified interaction criteria for use as candidate excipients in empirical screening studies.

A pharmaceutical composition for treating an influenza virus infectious disease, containing an anti-influenza virus agent as an active ingredient is provided. The anti-influenza virus agent is administered to a patient determined to be positive for the influenza virus infectious disease based on an intraoral image captured using an intraoral imaging apparatus.

Computer based methods, systems, and computer readable media for providing genomic services are provided. A request is received from a user. The request is applied to one or more from a group of a personalized data repository for the user and supporting knowledge bases, wherein the personalized data repository includes genetic test results, health/clinical information, and insurance coverage, and wherein the knowledge bases include information pertaining to genetic tests and clinical guidelines. Data from the applied request is integrated with results from service modules performing one or more from a group of content search, variation interpretation, and report generation to produce results for the request. The personalized data repository and supporting knowledge bases are updated based on the results of the request. Surveillance services are triggered based on one or more events.

Data that has been stored according to a DNA data storage method can be decoded using a flexible approach that supports both solitary strand mapping and cluster-based trace reconstruction. Solitary strand mapping can place strings based on integrity verification. Redundancy information can be partitioned to support error correction during the solitary strand mapping while still achieving integrity verification. Clusters with verified strands can be skipped during cluster-based trace reconstruction. Useful for increasing the accuracy of the trace reconstruction procedure.

Localized detection of RNA in a tissue sample that includes cells is accomplished on an array. The array include a number of features on a substrate. Each feature includes a different capture probe immobilized such that the capture probe has a free 3′ end. Each feature occupies a distinct position on the array and has an area of less than about 1 mm.sup.2. Each capture probe is a nucleic acid molecule, which includes a positional domain including a nucleotide sequence unique to a particular feature, and a capture domain including a nucleotide sequence complementary to the RNA to be detected. The capture domain can be at a position 3′ of the positional domain.