Abstract: Methods and associated apparatus involving designing a ligand ab initio that will bind to a binding site of a macromolecular target, or of identifying a modification to a ligand for improving the affinity of the ligand to a binding site of a macromolecular target, comprising using information about non-bonding, intra-molecular or inter-molecular atom to atom contacts extracted from a database of biological macromolecules to identify favoured regions adjacent to the binding site for particular atom types and modifying a candidate ligand to increase the intersection between atoms of the candidate ligand and the favoured regions. One or more steps of the methods may be performed by a computer.

Abstract: Technology provided herein relates in part to methods, processes, machines and apparatuses for non-invasive assessment of copy number alterations. In particular, a method is provided for determining presence or absence of a copy number alteration for a test subject. The method includes providing a set of sequence reads. The sequence reads may be obtained from circulating cell free sample nucleic acid from a test sample obtained from the test subject, and the circulating cell free sample nucleic acid may be captured by probe oligonucleotides under hybridization conditions. The method further includes determining a probe coverage quantification of the sequence reads for the probe oligonucleotides and determining the presence or absence of a copy number alteration in the circulating cell free sample nucleic acid based on the probe coverage quantification of the sequence reads for the probe oligonucleotides for the test sample.

Abstract: A method for compressing nucleic acid sequence data wherein each sequence read is associated with a molecular tag sequence, wherein a portion of the sequence reads alignments correspond to sequence reads mapped to a targeted fusion reference sequence includes determining a consensus sequence read for each family of sequence reads based on flow space signal measurements corresponding to the family of sequence reads, determining a consensus sequence alignment for each family of sequence reads, wherein a portion of the consensus sequence alignments correspond to the consensus sequence reads aligned with the targeted fusion reference sequence, generating a compressed data structure comprising consensus compressed data, the consensus compressed data including the consensus sequence read and the consensus sequence alignment for each family, and detecting a fusion using the consensus sequence reads and the consensus sequence alignments from the compressed data structure.

Abstract: Systems and methods for communicating, storing, and/or analyzing data that may include genomic data are described herein. In various embodiments, unaligned genomic sequence read data and/or portions thereof may be stored and/or communicated as a list of variants relative to a particular reference associated with a reference motif identified in the genomic sequence read data. In further embodiments, quality score information associated with a genomic dataset may be analyzed and/or communicated as quality score parameter information. Additional embodiments may facilitate relatively efficient analysis of unaligned genomic sequence read data using metadata associated with reference motifs identified in the unaligned genomic sequence read data.

Abstract: A large collection of sample genomes containing misclassified k-mers and metadata errors from a reference taxonomy was converted to a self-consistent k-mer database comprising a self-consistent taxonomy. The self-consistent taxonomy was based on genetic distances calculated using the MinHash method or the Meier-Koltoff method. An agglomerative clustering algorithm was used to calculate the self-consistent taxonomy. Each k-mer of the sample genomes was assigned to only one node of the self-consistent taxonomy. In another step, each node of the self-consistent taxonomy was mapped to the reference taxonomy, thereby preserving in the self-consistent taxonomy links to the reference taxonomy while correcting for the misclassification errors therein. The self-consistent k-mer database can be used to taxonomically profile sequenced nucleic acids with greater specificity compared to systems relying on the reference taxonomy.

Abstract: Systems and methods for multi-dimensional mapping of binary data DNA sequences are described. In one embodiment, the method may include determining a current level of a first DNA base from a sequence of DNA bases based at least in part on a read process of the sequence, determining a current level of a second DNA base after the first DNA base and a current level of a third DNA base after the second DNA base, and decoding binary data from the sequence based at least in part on the determined current level of the first DNA base, the determined current level of the second DNA base, and/or the determined current level of the third DNA base.

Abstract: The embodiments herein disclose a method and system for designing molecules by using a machine learning algorithm. The method includes representing molecular structures included in a dataset by using a Simplified Molecular Input Line Entry System (SMILES), where the SMILES uses a series of characters, converting a SMILES representation of the molecular structures into a binary representation, pre-training a stack of Restricted Boltzmann Machines (RBMs) by using the binary representation of the molecular structures, constructing a Deep Boltzmann Machine (DBM) by using the stack of the RBMs, determining limited molecular property data for a subset of the molecule structures in the dataset, training the DBM with the limited molecular property data, combining the pre-trained stack of the RBMs and the trained DBM in a Bayesian inference framework, and generating a sample of molecules with target properties by using the Bayesian inference framework.

Abstract: This disclosure describes an efficient method to copy all polynucleotides encoding digital data of digital files in a polynucleotide storage container while maintaining random access capabilities over a collection of files or data items in the container. The disclosure further describes a process whereby random-access and sequencing of the polynucleotides are combined in a single step.

Abstract: A whole cell model may be constructed and used to simulate cell behavior. The whole cell model may have a baseline cell state that can be perturbed by a user in order to understand the behavior and importance of various molecules, processes and/or sub-models within the whole cell model. The simulation data is evaluated according to a variety of heuristics. The simulation data is ranked within each heuristic. The heuristic evaluation of the simulation data is then compared to an input perturbation to determine the relative importance of the heuristics. The output is a visualization of the simulation data according to each heuristic within a dynamic ranked display.

Abstract: Polynucleotide sequencing generates multiple reads of a polynucleotide molecule. Many or all of the reads contain errors. Trace reconstruction takes multiple reads generated by a polynucleotide sequencer and uses those multiple reads to reconstruct accurately the nucleotide sequence of the polynucleotide molecule. Some reads may contain errors that cannot be corrected. Thus, there may be reads that can be used throughout their entire length and other reads that have indeterminant errors which cannot be corrected. Rather than discarding the entire read when an indeterminant error is found, the portion of the read with the error is skipped and the sequence of the read following the error is used to reconstruct the trace. The amount of the read skipped is determined by the location of subsequence after the error that matches a consensus sequence of the other reads. Analysis resumes at a location determined by the location of the match.