Abstract: The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.

Abstract: Systems, methods, and computer programs for analyzing genetic sequence data is disclosed. In one aspect, the system can include one or more of a first integrated circuit, with each first integrated circuit forming a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of a sequence analysis pipeline. Additionally, the system can include one or more second integrated circuits, with each second integrated circuit forming a field programmable gate array (FPGA). The FPGA can be configured by firmware to arrange a set of hardwired digital logic circuits to perform a second set of genomic processing stages of the sequence analysis pipeline, the set of hardwired digital logic circuits of each FPGA being arranged as a set of processing engines to perform the second set of genomic processing stages.

Abstract: Techniques are provided for replacing image assays using real world data and real word evidence RNA-seq analysis for assessing biologic pathways for identifying molecular subtypes. Systems of a methods diagnose HER2 status for a patient, by identifying discordant HER2 status result between the HER2 status from immunohistochemistry (IHC) and the HER2 status from fluorescence in-situ hybridization (FISH) and diagnosing HER2 status based gene expression data.

Abstract: Provided herein are methods and systems of molecular profiling of diseases, such as cancer. In some embodiments, the molecular profiling can be used to identify treatments for a disease, such as treatments that were not initially identified as a treatment for the disease or not expected to be a treatment for a particular disease.

Abstract: Biomarkers and methods using the biomarkers for the prediction of the recurrence risk of cancer in a patient are provided.

Abstract: Methods for targeting a tumor antigen for immunotherapy based on HLA allele type and the mutations present in the tumor antigen are presented. A patient's HLA allele type and a tumor antigen derived from a mutation in cancer driver gene can be matched with a majority allele type having a minimum affinity to the same tumor antigen or with those of a plurality of patients with a history of cancer treatment. Upon matching, a cancer treatment against the tumor antigen can be selected and administered to the patient to achieve a desired effect.

Abstract: A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes an integrated circuit formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the integrated circuit connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.

Abstract: A system, method and apparatus for executing a sequence analysis pipeline on genetic sequence data includes a integrated circuit formed of a set of hardwired digital logic circuits that are interconnected by physical electrical interconnects. One of the physical electrical interconnects forms an input to the integrated circuit connected with an electronic data source for receiving reads of genomic data. The hardwired digital logic circuits are arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired digital logic circuits to perform one or more steps in the sequence analysis pipeline on the reads of genomic data. Each subset of the hardwired digital logic circuits is formed in a wired configuration to perform the one or more steps in the sequence analysis pipeline.

Abstract: Methods and systems are provided for identifying drug compounds for targeting proteins in tissue cells. Such a method includes providing a neural network model which comprises an attention-based protein encoder and a molecular decoder. The protein encoder is pretrained in an autoencoder architecture to encode an input protein sequence into an output vector in a latent space representing proteins. The molecular decoder is pretrained in an autoencoder architecture to generate compound data, defining a compound molecule, from an input vector in a latent space representing molecules. The protein encoder and molecular decoder are coupled such that the input vector of the molecular decoder is dependent on the output vector of the protein encoder for an input protein sequence.

Abstract: A method for generating digital setups for an orthodontic treatment path. The method includes receiving a digital 3D model of teeth, performing interproximal reduction (IPR) on the model and, after performing the IPR, generating an initial treatment path with stages including an initial setup, a final setup, and a plurality of intermediate setups. The method also includes computing IPR accessibility for each tooth at each stage of the initial treatment path, applying IPR throughout the initial treatment path based upon the computed IPR accessibility, and dividing the initial treatment path into steps of feasible motion of the teeth resulting in a final treatment path with setups corresponding with the steps. The setups can be used to make orthodontic appliances, such as clear tray aligners, for each stage of the treatment path.

Abstract: Methods and apparatus for obtaining representations of proteins and small molecule drugs for synthesis; wherein input queries into trained mixed modality protein and natural language models are augmented with relevant query-related documents. In one embodiment, the relevant query-related documents are obtained by maximum inner product search of an embedding latent vector space into which the query and the documents are projected. The top-k most relevant documents to the query are then combined with the query as input into the trained mixed modality language model. In one embodiment, the mixed modality model is an autoregressive multicapitate transformer whose decoder output heads correspond to the represented modalities. The method returns mixed modality output representations of proteins or small molecule drugs for synthesis or manufacture.

Abstract: A method for nucleic acid sequencing includes receiving a plurality of observed or measured signals indicative of a parameter observed or measured for a plurality of defined spaces; determining, for at least some of the defined spaces, whether the defined space comprises one or more sample nucleic acids; processing, for at least some of the defined spaces, the observed or measured signal to improve a quality of the observed or measured signal; generating, for at least some of the defined spaces, a set of candidate sequences of bases for the defined space using one or more metrics adapted to associate a score or penalty to the candidate sequences of bases; and selecting the candidate sequence leading to a highest score or a lowest penalty as corresponding to the correct sequence for the one or more sample nucleic acids in the defined space.

Abstract: The present disclosure provides methods for determining a probability that after any of a number of therapeutic interventions, an initial state of a subject, such as somatic cell mutational status of a subject with cancer, will develop a subsequent state. Such probabilities can be used to inform a health care provider as to particular courses of treatment to maximize probability of a desired outcome for the subject.

Abstract: Time-series data formed by acquiring values indicating amounts or states of a plurality of biological materials for each biological material at a plurality of time points is prepared, the plurality of biological materials are divided into a plurality of groups on the basis of temporal variations of time-series data of the respective biological materials, representative time-series data indicating a state of each group is generated on the basis of time-series data of at least one biological material included in each group, and dependencies between the groups are estimated on the basis of the representative time-series data of each group.

Abstract: Methods, systems, and software are provided for determining a homologous recombination pathway status of a cancer in a test subject, e.g., to improve cancer treatment predictions and outcomes. In some embodiments, classifiers using one or more of (i) a heterozygosity status for DNA damage repair genes in a cancerous tissue, (ii) a measure of the loss of heterozygosity across the genome of the cancerous tissue, (iii) a measure of variant alleles detected in a second plurality of DNA damage repair genes in the genome of the cancerous tissue, (iv) a measure of variant alleles detected in the second plurality of DNA damage repair genes in the genome of a non-cancerous tissue, and (v) tumor sample purity are provided.

Abstract: Disclosed herein is a system and method for increasing the fidelity of measured genetic data, for making allele calls, and for determining the state of aneuploidy, in one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available. Poorly or incorrectly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related individuals. In accordance with one embodiment, incomplete genetic data from an embryonic cell are reconstructed at a plurality of loci using the more complete genetic data from a larger sample of diploid cells from one or both parents, with or without haploid genetic data from one or both parents. In another embodiment, the chromosome copy number can be determined from the measured genetic data, with or without genetic information from one or both parents.

Abstract: A plasma piwi-interacting RNA (piRNA) combination for early diagnosis of gastric cancer and application thereof are provided. Based on the plasma piRNA expression profile of the Chinese population, the present invention obtains a plasma piRNA combination for early diagnosis of gastric cancer, and establishes an early diagnosis model for gastric cancer based on the plasma piRNA combination. The model can predict the incidence risk of gastric cancer with relatively high accuracy, which helps to reduce the cost of detection. At the same time, the present invention uses a Lasso Logistic regression model, which greatly reduces the number of variables included in the model and facilitates the application and popularization of the model.

Abstract: A system and method for determining the genetic data for one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available, are disclosed. Genetic data for the target individual is acquired and amplified using known methods, and poorly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related subjects. In accordance with one embodiment of the invention, incomplete genetic data is acquired from embryonic cells, fetal cells, or cell-free fetal DNA isolated from the mother's blood, and the incomplete genetic data is reconstructed using the more complete genetic data from a larger sample diploid cells from one or both parents, with or without genetic data from haploid cells from one or both parents, and/or genetic data taken from other related individuals.

Abstract: Training a protein diffusion model includes receiving a representation of a protein as training data, the representation comprising at least three dimensions. It further includes training a protein diffusion model at least in part by performing rotational diffusion based at least in part on the representation of the protein. Generating proteins includes receiving protein conditioning information. It further includes, based at least in part on the protein conditioning information, performing conditional sampling of a protein diffusion model. The protein diffusion model is trained at least in part by performing rotational diffusion. Based at least in part on the conditional sampling of the protein diffusion model, the protein diffusion model generates one or more of a protein structure or a protein sequence.

Abstract: Integrated glucose monitoring systems, comprising a memory configured to store data relating to at least two glucose measurements of a user, a glucose safe range, and exogenous data. Wherein the at least two glucose measurements of the user are at different time points t1 and t2; a user interface comprising a display; and a processor comprising computer-executable instructions. Wherein the computer-executable instructions determine a rate of change based on the at least two glucose measurements of the user; determine, based on the at least two glucose measurements of the user and the determined rate of change, a projected glucose level at a future time t3; and provide an alarm at the user interface if, based on at least one point of exogenous data, the projected glucose level at future time t3 is outside of the glucose safe range.