Abstract: Methods and nucleic acid molecules for detecting chromosomal abnormalities such as aneuploidy. Methods for selecting nucleic acid molecules for use in the methods of the disclosure.

Abstract: The invention provides methods for determining aneuploidy and/or fetal fraction in maternal samples comprising fetal and maternal cfDNA by massively parallel sequencing. The method comprises a novel protocol for preparing sequencing libraries that unexpectedly improves the quality of library DNA while expediting the process of analysis of samples for prenatal diagnoses.

Abstract: The present invention relates generally to a method of determining one or more probabilities of respective classifications of a neoplasm into one or more neoplastic categories. More particularly, the present invention relates to a method of determining the probability of classification of a large intestine neoplasm into one or more categories selected from adenoma, stage I, stage II, stage III or stage IV by screening for changes to the methylation levels of a panel of gene markers, including BCAT1, IKZF1, IRF4, GRASP and/or CAHM. The method of the present invention is useful in a range of applications including, but not limited to, those relating to the diagnosis and/or monitoring of colorectal neoplasms, such as colorectal adenocarcinosis.

Abstract: This invention relates to molecular diagnostics and, more specifically DNA-based tests for the prognosis and/or monitoring of fibrotic disease progression in humans, and processes for stratifying patients based on their likely rates of fibrotic disease progression. The invention also relates to the field of therapy for fibrotic disease, based on such prognoses, monitoring and stratification results, such as in monitoring and/or stratifying and/or treating patients having a higher likelihood of rapid fibrotic disease progression.

Abstract: Methods, systems and computer-readable storage media relate to generating one or more consensus sequences. The methods may include determining a group of one or more reads with each main position without diversity from a group of one or more aligned reads based on diversity status of each main position, each group including sequence data disposed at a plurality of main positions and a plurality of secondary position regions disposed adjacent to the main positions. The methods may also include determining legitimate sequence data from each second position region having one or more nucleotides for each group of one or more reads without diversity; and generating a consensus sequence including sequence data disposed at each main position without diversity and legitimate sequence data disposed at each secondary position region for each group of one or more reads with each main position without diversity.

Abstract: Artificial polynucleotides may have different characteristics than natural polynucleotides so conventional base-calling algorithms may make incorrect base calls. However, because artificial polynucleotides are typically designed to have certain characteristics, the known characteristics of the artificial polynucleotide can be used to modify the base-calling algorithm. This disclosure describes polynucleotide sequencers adapted to sequence artificial polynucleotides by modifying a base-calling algorithm of the polynucleotide sequencer according to known characteristics of the artificial polynucleotides. The base-calling algorithm analyzes raw data generated by a polynucleotide sequencer and identifies which nucleotide base occupies a given position on a polynucleotide strand.

Abstract: In embodiments of latent space harmonization (LSH) for predictive modeling, different training data sets are obtained from different measurement methods, where input data among the training data sets is quantifiable in a common space but a mapping between output data among the training data sets is unknown. A LSH module receives the training data sets and maps a common supervised target variable of the output data to a shared latent space where the output data can be jointly yielded. Mappings from the shared latent space back to the output training data of each training data set are determined and used to generate a trained predictive model. The trained predictive model is useable to predict output data from new input data with improved predictive power from the training data obtained using various, otherwise incongruent, measurement techniques.

Abstract: In various embodiments, an information storage system comprises: a writing device for synthesizing a nucleotide sequence that encodes a set of information; and a reading device for interpreting the nucleotide sequence by decoding the interpreted nucleotide sequence into the set of information, wherein the reading device comprises a molecular electronics sensor, the sensor comprising a pair of spaced apart electrodes and a molecular complex attached to each electrode to form a molecular electronics circuit, wherein the molecular complex comprises a bridge molecule and a probe molecule, and wherein the molecular electronics sensor produces distinguishable signals in a measurable electrical parameter of the molecular electronics sensor, when interpreting the nucleotide sequence.

Abstract: Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of nucleic acid fragments from circulating cell free nucleic acid. Also provided herein are methods for partitioning one or more genomic regions of a reference genome into a plurality of portions according to one or more features.

Abstract: Generation of biomolecule sequence coevolution data structures, matrices, scores, and sectors are described. Generally, the generated coevolution data removes covariant noise due to phylogenetic drift and can reveal coevolution of residue positions in multiple phylogenetic distances. Scores can be built upon the data structures and matrices to reveal sectors of residue positions that function and evolve together. Furthermore, the coevolution data structures, matrices, scores, and sectors can be used to predict structure or function of residue variants.

Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: Continuous glucose monitoring (CGM) data and insulin delivery data are used to generate more reliable projected alarms related to a projected glucose levels. A memory stores endogenous data related to measurements of glucose level in a patient, and also stores exogenous data, such as insulin on board, both of which are used by a processor to create projected alarms. Profiles of CGM data are created for use in tuning patient-specific insulin data, such at basal rate, carb ratio, and insulin sensitivity. A processor searches for patterns in the data profiles and if found, recommended changes to patient-specific insulin data are provided to permit more accurate control over a patient's glucose levels.

Abstract: The present invention provides a method for genotyping alleles in at least one homologous genetic loci set, comprising: (i) providing a DNA-containing sample that includes said at least one homologous genetic loci set; (ii) performing PCR amplification of regions of said homologous genetic loci set using consensus sequence-specific primers, wherein said consensus sequence-specific primers bind to consensus sequences that are common to a plurality of genes within the genetic loci set, thereby generating a pool of amplification products; (iii) sequencing a plurality of said amplification products in order to determine the relative proportion of each nucleotide at each position in a sequencing read; (iv) performing a sequence alignment between the sequencing read results of (iii) and at least one reference sequence, which reference sequence corresponds to one of the genes in said homologous genetic loci set; and (v) performing genotype calling of the allele or alleles in said sample based on the relative proport

Abstract: Methods for analyzing signal data generated by sequencing of a polynucleotide strand using a pH-based method of detecting nucleotide incorporation(s). In an embodiment, the method comprises formulating a function that models the output signal of a representative empty well of a reactor array. A time transformation is applied to the empty well function to obtain a time-warped empty well function. The time-warped empty well function is fitted to an output signal from the loaded well representative of a flow that results in a non-incorporation event in the loaded well. The fitted time-warped empty well function can then be used to analyze output signals from the loaded well for other flows.

Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: A sequence data analyzer comprising: a read dictionary preparation unit creating a read sequence dictionary based on a concatenation string, the concatenation string constituted of a pair of a left sequence and a right sequence, which are obtained by sequencing a sample DNA fragment respectively from the left and right ends, and connecting characters connecting these sequences together; and a sample reconstruction unit extracting, as a sample sequence, a string up to a terminal character positioned in the string of a hit position of a query sequence in the read sequence dictionary, and extracting, as a mate sequence, the left sequence or right sequence until the appearance of a terminal character on the side where the hit position doesn't exist in the sample sequence.

Abstract: The present disclosure provides a HTP microbial genomic engineering platform that is computationally driven and integrates molecular biology, automation, and advanced machine learning protocols. This integrative platform utilizes a suite of HTP molecular tool sets to create HTP genetic design libraries, which are derived from, inter alia, scientific insight and iterative pattern recognition. The HTP genomic engineering platform described herein is microbial strain host agnostic and therefore can be implemented across taxa. Furthermore, the disclosed platform can be implemented to modulate or improve any microbial host parameter of interest.

Abstract: This invention relates to automatic insulin delivery systems and methods of administering insulin. Preferably the systems and methods comprise a predictive feedforward control.

Abstract: Exemplary embodiments provide methods and systems for diploid genome assembly and haplotype sequence reconstruction. Aspects of the exemplary embodiment include generating a fused assembly graph from reads of both haplotypes, the fused assembly graph including identified primary contigs and associated contigs; generating haplotype-specific assembly graphs using phased reads and haplotype aware overlapping of the phased reads; merging the fused assembly graph and haplotype-specific assembly graphs to generate a merged assembly haplotype graph; removing cross-phasing edges from the merged assembly haplotype graph to generate a final haplotype-resolved assembly graph; and reconstructing haplotype-specific contigs from the final haplotype-resolved assembly graph resulting in haplotype-specific contigs.

Abstract: This disclosure describes frameworks and techniques related to the random access of digital data encoded by polynucleotides. Digital data of a data file can be encoded as a series of nucleotides and one or more polynucleotide sequences can be generated that encode the digital data for the data file. The bits of the digital data can be segmented to produce multiple polynucleotide sequences that encode the bits of the digital data with each polynucleotide sequence encoding an individual segment of the digital data. The individual segments can be grouped together and associated with a group identifier. Each data file can be associated with a number of group identifiers and the number of segments in each group can be within a specified range. Primers corresponding to the group identifiers can be used to selectively access the polynucleotides that encode the digital data of a data file.