In variants, a method for automated gamete selection can include: sampling a video of a scene having a plurality of gametes, tracking each gamete across successive images, and determining attribute values for a gamete, and selecting the gamete. The attribute values can be determined using a model trained to predict the attribute values for the gamete based on a video.

A system and method that produces an accurate probability distribution representative of a target molecule that may be used in pharmacokinetics and analogous applications. A generator is seeded from a variational autoencoder during training and is then used after training in series with a second variational autoencoder to produce the probability distributions from molecular tensors.

A system and method that produces an accurate probability distribution representative of a target molecule that may be used in pharmacokinetics and analogous applications. A generator is seeded from a variational autoencoder during training and is then used after training in series with a second variational autoencoder to produce the probability distributions from molecular tensors.

The present disclosure provides a novel approach for shifting or distributing various information (e.g., protocols, analysis methods, sample preparation data, sequencing data, etc.) to a cloud-based network. For example, the techniques relate to a cloud computing environment configured to receive this information from one or more individual sample preparation devices, sequencing devices, and/or computing systems. In turn, the cloud computing environment may generate information for use in the cloud computing environment and/or to provide the generated information to the devices to guide a genomic analysis workflow. Further, the cloud computing environment may be used to facilitate the sharing of sample preparation protocols for use with generic sample preparation cartridges and/or monitoring the popularity of the sample preparation protocols.

A method for at least one of characterizing, diagnosing, and treating an autoimmune disorder in at least a subject, the method comprising: receiving an aggregate set of biological samples from a population of subjects; generating at least one of a microbiome composition dataset and a microbiome functional diversity dataset for the population of subjects; generating a characterization of the autoimmune condition based upon features extracted from at least one of the microbiome composition dataset and the microbiome functional diversity dataset; based upon the characterization, generating a therapy model configured to correct the autoimmune condition; and at an output device associated with the subject, promoting a therapy to the subject based upon the characterization and the therapy model.

Provided are systems and methods for rational selection of context sequences and sequence templates including a computer implemented method for obtaining a repository of attributes sets where the attributes sets are statistically associated with a sequence template representing two or more context sequences.

An ontology matching apparatus for large-scale biomedical ontologies according to the present invention is provided, and the ontology matching apparatus includes a preprocessing unit configured to classify received candidate ontologies into one or more ontology subsets to generate ontology subsets, a distribution processing unit configured to divide the generated ontology subsets by virtue of a distribution algorithm, apply a matching algorithm to the divided ontology subsets to generate matching threads, and deliver the generated matching threads to individual cores of participating nodes, and an aggregating unit configured to collect and sum matching results generated by the individual cores performing matching operations based on the matching threads to generate an ontology mapping.

Systems and methods for conducting secure, privacy-preserving, verifiable omic transactions are provided. An omic service may authenticate one or more individual users and store each users omic information as encrypted data, without storing decryption keys, and also ensure fidelity and correct correspondence of each user's data with the user. A dedicated private virtual appliance can be instantiated to obtain encrypted omic data, query each user for decryption keys, decrypt the user omic data, perform an omic calculation, report results and terminate itself, thereby erasing all copies of decrypted user omic data. Alternatively, the appliance can operate with user-managed genome storage. A genome-on-a-stick construct facilitates end user interaction with such omic service providers.

A software development tool uses a workflow pattern that describes software applications. The tool may provide a solution that can automatically generate a well-architected application without compromising its quality or integrity. The tool may have a Data Notation Architecture (DNA) layer and a Resolution Notation Architecture (RNA) layer Genetic Framework that use a workflow pattern that describes software applications. Models may be identified and linked together using a Polymorphic Relational Path Language (PRPL), which is a scripting language that is designed and optimized to resolve various hierarchy and set theory problems that naturally appear in programming. When targeting the Service Area Architecture Pattern (SAAP), this Genetic Framework may greatly reduce the overall cost of virtually every part of the software development lifecycle.

An embodiment of a system and method for characterizing a Clostridium-associated condition in relation to a user includes: a handling network operable to receive containers including material from a set of users, the handling network including a sequencing system operable to determine microbiome sequences from sequencing the material; a processing system operable to generate a microbiome composition dataset and a microbiome functional diversity dataset based on the microbiome sequences, receive a supplementary dataset associated with the Clostridium-associated condition for the set of users; transform the supplementary dataset and features extracted from the microbiome composition dataset and the microbiome functional diversity dataset into a characterization model for the Clostridium-associated condition; and a therapy system operable to promote a therapy to the user based on characterizing the user in relation to the Clostridium-associated condition using the characterization model.