Abstract: Systems and techniques for extracting information-containing payloads from DNA or other polynucleotides are provided. Decoding the sequence of payload regions from multiple polynucleotides to obtain encoded information includes sequencing the molecules with a polynucleotide sequencer. Reads generated by the polynucleotide sequencer can include information from multiple different sources mixed together. Primer sequences present in the reads identify which reads contain information from the same source. A computationally efficient technique for finding primer sequences in the reads includes comparing hashes of the reads and hashes of primer sequences to find an approximate location then computing edit distances between the primer sequences and the reads to find an exact location. Reads that include the same primer sequences may be clustered together. Sequences of the payload regions are extracted based on the locations of the primer sequences.

Abstract: Systems and methods for analyzing first and second strings against a ground truth string are provided. A construct representing a plurality of components is obtained, each component for a different portion of the truth string. The construct comprises a plurality of measurement string sampling pools each having an identifier and a corresponding plurality of measurement samplings corresponding to one or two of the components. Each sampling has the identifier and a portion of the first or second string. Samplings are assigned to first, second or third classes when coding a portion of the first string, second string, or both the first and second string. First and second positions are tested for sequence events by calculating a plurality of sequence event models using assumptions on the components having samplings encompassing the first and second positions and class assignments. These assumptions are updated using the calculated models and the models are recalculated.

Abstract: A scaffold-oriented line notation can include: a scaffold sequence of atom identifiers of a scaffold, the scaffold sequence includes at least one decoration marker or any number of decoration markers, each decoration marker being adjacent to an atom identifier of a linking atom of the scaffold; a decoration separator following a last atom identifier or a last decoration marker of the scaffold sequence; at least one decoration having at least one atom identifier in a line notation that defines a chemical structure of the chemical moiety of the decoration that is attached to the linking atom of the scaffold of the molecule; in the scaffold sequence, an order of the at least one decoration marker defines an order of the at least one decoration; in the at least one decoration, the first decoration follows the first decoration separator.

Abstract: Presented herein are techniques for identifying and/or validating sequence variants in genomic sequence data. The techniques include generating an error rate reflective of sequence errors present in the genomic sequence data. The error rate may be used to validate potential sequence variants. The error rate may be based on errors identified during consensus sequence confirmation for sequence reads associated with individual unique molecular identifiers.

Abstract: A peeling type laser tooth preparing method, apparatus and device, and a medium. Method comprises: acquiring a first STL model of a target tooth and a second STL model of a tooth preparation of the target tooth; generating a conical peeling curved-surface STL model, in a manner of taking a three-dimensional curve of a peripheral edge contour of a shoulder in the second STL model as a bottom edge; carrying out Boolean calculation on the peeling curved-surface STL model and the first STL model to obtain a third STL model; carrying out Boolean calculation on the second STL model and the third STL model to obtain a fourth STL model required to be removed; generating a multilayer laser cutting path according to the fourth STL model, controlling a laser tooth preparing device to perform the tooth preparing process of the target tooth according to the multilayer laser cutting path.

Abstract: An analytics system creates a data structure counting strings of methylation vectors from a healthy control group. The analytics system enumerates possibilities of methylation state vectors given a sample fragment from a subject, and calculates probabilities for all possibilities with a Markov chain probability. The analytics system generates a p-value score for the subject's test methylation state vector by summing the calculated probabilities that are less than or equal to the calculated probability of the possibility matching the test methylation state vector. The analytics system determines the test methylation state vector to be anomalously methylated compared to the healthy control group if the p-value score is below a threshold score. With a number of such sample fragments, the analytics system can filter the sample fragments based on each p-value score. The analytics system can run a classification model on the filtered set to predict whether the subject has cancer.

Abstract: Humanizing proteins can be a laborious process, often involving trial and error or other non-systematic methods. To improve humanization, neural networks can be employed to generate new protein sequences having higher probabilities of being humanized. In an embodiment, a method includes evaluating the immunogenicity of a sampling of protein sequences. The method can include weighting the sampling of protein sequences from the generative model according to an estimated probability of a particular generated protein sequence having a deviation in immunogenicity than a particular percentile of immunogenicity of the sampling of protein sequences. The method can further include generating a protein sequence weighted sampling of protein sequences. The generated protein sequence representing a protein has an altered immunogenicity. Such a generated protein has a higher likelihood of being humanized.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for searching chemical structures. One of the methods includes receiving a fingerprint map for each chemical structure of a collection of chemical structures, generating an inverted index for the collection of chemical structures, receiving a request to search the inverted index for matching chemical structures, obtaining a query fingerprint for the query structure, computing a minimum number of bits and a maximum number of bits that must be present in respective fingerprints of candidate structures in the collection of chemical structures in order for a candidate structure to be considered a match for the query structure, and traversing the inverted index to identify candidate structures having fingerprints with a number of bits in between the minimum number of bits and the maximum number of bits.

Abstract: A technique for clustering DNA reads from polynucleotide sequencing is described. DNA reads with a level of difference that is likely caused by errors in sequencing are grouped together in the same cluster. DNA reads that represent reads of different DNA molecules are placed in different clusters. The clusters are based on edit distance, which is the number of changes necessary to convert a given DNA read into another. The process of forming clusters may be performed iteratively and may use other types of distance that serve as an approximation for edit distance. Well clustered DNA reads provide a starting point for further analysis.

Abstract: A genomic data analyzer may be configured to detect and characterize, with a variant calling module, genomic variant scenarios in sequencing reads from an enriched patient genomic sample comprising a combination of a first repeat pattern and a second repeat pattern, such as repeats of homopolymer (single nucleotide) and/or heteropolymer (multiple nucleotide) basic motifs. The variant calling module may estimate the probability distribution of the length of the first repeat pattern and the probability distribution of the length of the second repeat pattern by comparing the distribution of the repeat pattern length measurements in patient data to the distribution of the repeat pattern length measurements in control data, in order to remove biases possibly induced by the next generation sequencing laboratory setup both in control and patient data.

Abstract: Exemplary systems and methods for selecting from population of candidate edits and predicting an aggregate effect of the candidate edits are disclosed. One exemplary method includes identifying a population of candidate edits to a genomic sequence of said organism and ranking each of the candidate edits based on a predicted ability of each candidate edit to affect a trait of interest in said organism. The exemplary method further includes selecting one or more of the candidate edits based on the ranking and predicting, by the computing device, an aggregate effect of the selected one or more of the candidate edits for the trait of interest when expressed by a specimen of the organism having a genomic sequence and edited according to the selected one or more of the candidate edits, as compared to an unedited specimen of the organism.

Abstract: An identification apparatus acquires a protein file in which a plurality of proteins including a plurality of amino acids are arranged. The identification apparatus identifies a plurality of primary structure candidates with any position included in the protein file as a starting position. The identification apparatus identifies one primary structure among the primary structure candidates based on a combination of a primary structure and each amino acid and a primary structure table, where the each amino acid is positioned at an end of the primary structure and the primary structure table associates a primary structure and a cooccurrence rate of a certain amino acid combination positioned at an end of the primary structure.

Abstract: Methods, systems and circuits evaluate a subject's CVD risk using a risk parameter that includes at least one HDL and inflammatory biomarker interaction parameter. The inflammatory biomarker may optionally comprise NMR derived measurements of GlycA from at least one biosample of the subject. The risk parameter may be gender-specific.

Abstract: Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes using defined mathematical models of short term risk (STR) and longer term risk of progression. The evaluations can stratify risk for patients having the same glucose measurement, particularly those with intermediate or low (normal) fasting plasma glucose (FPG) values. The STR or IR (insulin resistance) model(s) may include an inflammatory biomarker such as an NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. Embodiments of the invention also provide methods, systems and circuits that generate STR scores as a marker of beta-cell dysfunction or impairment.

Abstract: Embodiments predict response to neoadjuvant chemotherapy (NAC) in breast cancer (BCa) from pre-treatment dynamic contrast enhanced magnetic resonance imaging (DCE-MRI).

Abstract: Systems, devices and methods for predicting binding on an array such as a peptide array. Certain methods utilize a peptide array having a plurality of peptides with one or more defined parameters and contacting the peptide array with a training sample containing one or more molecules of interest. Interactions between the plurality of peptides and the one or more molecules of interest are processed according to a data fitting model, which model is then is applied to interactions between the plurality of peptides and a test sample to predict binding associated with the one or more molecules of interest.

Abstract: A big data-based intelligent algorithm for an intraoral prosthesis design scheme establishes an intraoral prosthesis design scheme database based on predetermined data of partially edentulous jaw, and is configured to conduct an accurate search for data of partially edentulous jaw to obtain a recommendation list of an accurate theme and a corresponding design scheme for an intraoral prosthesis design, or conduct a fuzzy search for data of partially edentulous jaw to obtain a recommendation list of a fuzzy theme and a corresponding design scheme for an intraoral prosthesis design. When oriented to a digital design of a removable partial denture, the intelligent system for the intraoral prosthesis design scheme constructed based on this intelligent algorithm displays a large number of intraoral prosthesis design schemes of different design themes to dental technicians in a three-dimensional manner.

Abstract: A machine learning system and method for somatic mutation discovery are provided that provides improved identification of tumor-specific mutations. The improved identification of tumor-specific mutations may affect discovery of alterations and therapeutic management of cancer patients.

Abstract: The subject disclosure presents systems and computer-implemented methods for determining an acoustic time-of-flight (TOF) of sound waves through a sample material with greater accuracy and in a more repeatable fashion, by invoking one or more of an envelope generation for an error function, fitting a non-linear curve to an ultrasound frequency sweep, or performing a clustered piece-wise linear regression on individual linear parts of the ultrasonic frequency sweep. The systems and methods are useful for, among other things, monitoring diffusion of fluids through porous materials, such as tissue samples.

Abstract: A method and a system for calculating tumor neoantigen burden (TNB) are provided. The method includes: step S1: processing a normal sample and a tumor sample, sequencing a specific region and detecting somatic mutations in the sample; step S2: annotating and filtering the somatic mutations, and translating to obtain mutant peptide sequences of a patient; step S3: filtering the mutant peptide sequences to obtain neopeptide sequences based on a proteome of the normal sample; step S4, performing a human leukocyte antigen (HLA) typing analysis based on alignment data of the normal sample to obtain HLA genotypes of the sample; step S5, predicting binding affinities between the neopeptide sequences and the HLA genotypes to obtain specific neoantigens of the sample, and performing a weighted scoring on each of the specific neoantigens and calculating the TNB of the sample.