Abstract: Provided herein are compositions, methods, and systems for sample processing and/or data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample from a human, non-human, and combinations thereof.

Abstract: The disclosure provides methods for predicting surface-presenting peptides using binding and surface-presentation characteristics. The method can include accessing a trained machine-learning model that is configured to generate an output that indicates an extent to which the one or more expression levels and the one or more peptide-presentation metrics are related in accordance with a population-level relationship between expression and presentation. For each peptide of the set of peptides for a tissue sample, a score can be determined using the machine-learning model and genomic and transcriptomic data corresponding to the peptide. The score is predictive of whether a corresponding peptide is a surface-presenting peptide that binds to an MHC molecule and is presented on a cell surface.

Abstract: The present disclosure provides methods and systems for personalized genetic testing of disease in a subject, in particular for identifying and tracking genetic mutations identified in an individual subject to monitor for cancer or for the spread or recurrence of the disease. In some embodiments, custom assays, including custom panels designed to target sequence data corresponding to both subject-specific loci and other loci known for cancer-causing or therapy resistance mutations, are designed based upon the sequencing of a screening biopsy sample. Such custom assays are then run on subsequently obtained tissue samples, such as tissue obtained from a surgical resection of a primary or metastatic tumor or from a lymph node biopsy. The subsequently obtained tissue samples can be taken from the subject at various time points after an initial screening biopsy to further allow for extended monitoring of the subject for spread or recurrence of the disease.

Abstract: This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

Abstract: This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

Abstract: Methods for generating a composite biomarker that identifies a predicted level of responsiveness of a subject to a particular type of an immunotherapy treatment is provided. The method can include generating genomic metrics that represent one or more characteristics corresponding to one or more DNA sequences. The method can also include generating transcriptomic metrics represent one or more characteristics corresponding to a set of peptides that are translated from a corresponding RNA sequence of the one or more RNA sequences. The method can also include generating a composite biomarker score derived from the set of genomic metrics and the set of transcriptomic metrics. The method can also include determining, based on the composite biomarker score, a predicted level of responsiveness of the subject to a particular type of an immunotherapy treatment.

Abstract: A biodegradable polymer usable in fishing gear and that biodegrades in aquatic environments. The polymer includes a polymer backbone that has monomeric units that are susceptible to hydrolytic degradation, and a plurality of pH responsive moieties. Each pH responsive moiety is grafted to a respective one of the monomeric units. The pH responsive moieties are relatively hydrophilic when exposed to an aqueous solution of a pro-biodegradation pH range to facilitate hydrolytic degradation of the monomeric units, and are relatively hydrophobic when removed from the aqueous solution of the pro-biodegradation pH range, to protect the monomeric units from hydrolytic degradation.

Abstract: In one or more embodiments described herein, device, computer-implemented methods, and/or computer program products that facilitate automated survey results generation from an image are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an image capturing component that captures a first sample image. The computer executable components can further comprise an image processing component that processes the first sample image to determine a survey count, wherein the survey count indicates a number of times a survey image was identified in the first sample image. The computer executable components can further comprise an authentication component that adjusts the survey count based on detection of a discrepancy.

Abstract: A hybrid-distance adversarial patch generator can be trained to generate a hybrid adversarial patch effective at multiple distances. The hybrid patch can be inserted into multiple sample images, each depicting an object, to simulate inclusion of the hybrid patch at multiple distances. The multiple sample images can then be used to train an object detection model to detect the objects.

Abstract: Techniques regarding quantum computation of molecular excited states are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise an initialization component that can categorize a plurality of excited operators from a mapped qubit Hamiltonian into sectors based on a commutation property of the plurality of excited operators with a symmetry from the mapped qubit Hamiltonian. The computer executable components can also comprise a matrix component that can generate an equation of motion matrix from an excited operator from the plurality of excited operators based on the sectors categorized by the initialization component.

Abstract: A hybrid classical-quantum computing device to execute a quantum circuit corresponding to a variational problem, is configured. The configuring further comprises causing the hybrid classical-quantum computing device to execute the quantum circuit by performing an adiabatic progression operation, wherein the adiabatic progression operation comprises increasing the difficulty of the variational problem from a simplified version of the problem to the variational problem.

Abstract: A hybrid classical-quantum computing device to execute a quantum circuit corresponding to a variational problem, is configured. The configuring further comprises causing the hybrid classical-quantum computing device to execute the quantum circuit by performing an adiabatic progression operation, wherein the adiabatic progression operation comprises increasing the difficulty of the variational problem from a simplified version of the problem to the variational problem.

Abstract: A computer-implemented method for processing and/or analyzing nucleic acid sequencing data comprises receiving a first data input and a second data input. The first data input comprises untargeted sequencing data generated from a first nucleic acid sample obtained from a subject. The second data input comprises target-specific sequencing data generated from a second nucleic acid sample obtained from the subject. Next, with the aid of a computer processor, the first data input and the second data input are combined to produce a combined data set. Next, an output derived from the combined data set is generated. The output is indicative of the presence or absence of one or more polymorphisms of the first nucleic acid sample and/or the second nucleic acid sample.

Abstract: A distributed database management system comprises a plurality of peers and maintains data on behalf of a plurality of clients. Upon receiving a request to access data, the distributed database management system identifies, from among the plurality of peers, a set of peers associated with the client issuing the request. The distributed database management system provides, to the client, a list of the set of identified peers. Access to data maintained by the distributed database system is based, at least in part, on connections between the client and the set of identified peers.

Abstract: Systems and methods can quantify the tumor microenvironment for diagnosis, prognosis and therapeutic response prediction by fusing different data types (e.g., morphological information from histology and molecular information from omics) using an algorithm that harnesses deep learning. The algorithm employs tensor fusion to provide end-to-end multimodal fusion to model the pairwise interactions of features across multiple modalities (e.g., histology and molecular features) and deep learning. The systems and methods improve upon traditional methods for quantifying the tumor microenvironment that rely on concatenation of extracted features.

Abstract: A distributed database system maintains data for a logical table by storing, on a plurality of storage nodes, a collection of key-item pairs. The distributed database system receives a query of the logical table, and identifies one or more portions of a key specified by the query. Based on the one or more portions of the key, the distributed database causes at least one of a get, range query, or scan operation to be performed by one or more of the storage nodes. Results for the query are generated based on one or more items obtained by performance of the operation.

Abstract: A computer-implemented method for processing and/or analyzing nucleic acid sequencing data comprises receiving a first data input and a second data input. The first data input comprises untargeted sequencing data generated from a first nucleic acid sample obtained from a subject. The second data input comprises target-specific sequencing data generated from a second nucleic acid sample obtained from the subject. Next, with the aid of a computer processor, the first data input and the second data input are combined to produce a combined data set. Next, an output derived from the combined data set is generated. The output is indicative of the presence or absence of one or more polymorphisms of the first nucleic acid sample and/or the second nucleic acid sample.

Abstract: One embodiment of the invention provides a method for video recognition. The method comprises receiving an input video comprising a sequence of video segments over a plurality of data modalities. The method further comprises, for a video segment of the sequence, selecting one or more data modalities based on data representing the video segment. Each data modality selected is optimal for video recognition of the video segment. The method further comprises, for each data modality selected, providing at least one data input representing the video segment over the data modality selected to a machine learning model corresponding to the data modality selected, and generating a first type of prediction representative of the video segment via the machine learning model. The method further comprises determining a second type of prediction representative of the entire input video by aggregating all first type of predictions generated.

Abstract: A computer-implemented method for processing and/or analyzing nucleic acid sequencing data comprises receiving a first data input and a second data input. The first data input comprises untargeted sequencing data generated from a first nucleic acid sample obtained from a subject. The second data input comprises target-specific sequencing data generated from a second nucleic acid sample obtained from the subject. Next, with the aid of a computer processor, the first data input and the second data input are combined to produce a combined data set. Next, an output derived from the combined data set is generated. The output is indicative of the presence or absence of one or more polymorphisms of the first nucleic acid sample and/or the second nucleic acid sample.

Abstract: This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.