Abstract: Provided herein are novel methods, systems and processes for mapping sequence reads to a modified reference genome and determining the presence or absence of a genetic variation, or the likelihood thereof, in a gene of interest in a subject.

Abstract: A method includes performing a nucleic acid amplification of a nucleic acid sample using a detection probe, wherein the nucleic acid amplification occurs over one or more interrogation periods, and, from the nucleic acid amplification, acquiring amplification data that indicates an amount of nucleic acid present for each of the one or more interrogation periods. The method also includes, based on the amplification data, determining a crosstalk correction value associated with a spectral neighbor to the probe to reduce spectral crosstalk from the spectral neighbor; and applying the crosstalk correction value to amplification data collected from multiplex nucleic acid amplifications of nucleic acid samples.

Abstract: A method of predicting whether an MDS patient has a good or poor prognosis uses a general purpose computer configured as a classifier and mass-spectrometry data obtained from a blood-based sample. The classifier assigns a classification label of either Early or Late (or the equivalent) to the patient's sample. Patients classified as Early are predicted to have a poor prognosis or worse survival whereas those patients classified as Late are predicted to have a relatively better prognosis and longer survival time. The groupings demonstrated a large effect size between groups in Kaplan-Meier analysis of survival. Most importantly, while the classifications generated were correlated with other prognostic factors, such as IPSS score and genetic category, multivariate and subgroup analysis showed that they had significant independent prognostic power complementary to the existing prognostic factors.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

Abstract: Methods for identifying compounds that are inhibitors or are likely to be inhibitors of amyloid protein aggregation, as well as three-dimensional, non-crystallographic models (i.e. “pseudo-crystal structures”) of amyloid aggregation utilized in the methods, are described. Means for creating the three-dimensional, non-crystallographic models (i.e. “pseudo-crystal structures”) of amyloid aggregation are also described.

Abstract: Disclosed is a method for analyzing a sulfide-based solid electrolyte using computer simulation including connecting, by a user, to a client accessible to a server, inputting information of a sulfide-based solid electrolyte to be analyzed to the client, transmitting, by the client, the information to the server, implementing, by the server, generation of a three-dimensional structure in which anion clusters and lithium ions are disposed, based on the transmitted information, feeding back, by the server, an implementation result to the client, and displaying, by the client, the feedback result. In addition, properties of sulfide-based solid electrolytes, which cannot be observed by experimentation, can be analyzed based on lithium, ion conductivity.

Abstract: A method and system for calculating the free energy difference between a target state and a reference state. The method includes determining one or more intermediate states using a coupling parameter, performing molecular simulations to obtain ensembles of micro-states for each of the system states, and calculating the free energy difference by an analysis of the ensembles of micro-states of the system states. The method can be particularly suited for calculating physical or non-physical transformation of molecular systems such as ring-opening, ring-closing, and other transformations involving bond breaking and/or formation. A soft bond potential dependent on a bond stretching component of the coupling parameter and different from the conventional harmonic potential is used in the molecular simulations of the system states for the bond being broken or formed during the transformation.

Abstract: The invention provides oncogenomic methods for detecting tumors by identifying circulating tumor DNA. A patient-specific reference directed acyclic graph (DAG) represents known human genomic sequences and non-tumor DNA from the patient as well as known tumor-associated mutations. Sequence reads from cell-free plasma DNA from the patient are mapped to the patient-specific genomic reference graph. Any of the known tumor-associated mutations found in the reads and any de novo mutations found in the reads are reported as the patient's tumor mutation burden.

Abstract: A method includes obtaining, from one or more sequencing devices, raw data detected from luminescent labels associated with nucleotides during nucleotide incorporation events; and processing the raw data to perform a comparison of base calls produced by a learning enabled, automatic base calling module of the one or more sequencing devices with actual values associated with the raw data, wherein the base calls identify one or more individual nucleotides from the raw data. Based on the comparison, an update to the learning enabled, automatic base calling module is created using at least some of the obtained raw data, and the update is made available to the one or more sequencing devices.

Abstract: Described are techniques for determining population structure from identity-by-descent (IBD) of individuals. The techniques may be used to predict that an individual belongs to zero, one or more of a number of communities identified within an IBD network. Additional data may be used to annotate the communities with birth location, surname, and ethnicity information. In turn, these data may be used to provide to an individual a prediction of membership to zero, one or more communities, accompanied by a summary of the information annotated to those communities.

Abstract: A method for efficient search of protein sequence databases for proteins that have sequence, structural, and/or functional homology with respect to information derived from a search query. The method involves transforming the protein sequences into vector representations and searching in a vector space. Given a database of protein sequences and a learned embedding model, the embedding model is applied to each amino acid sequence to transform it into a sequence of vector representations. A query sequence is also transformed into a sequence of vector representations, preferably using the same learned embedding model. Once the query has been embedded in this manner, proteins are retrieved from the database based on distance between the query embedding and the protein embeddings contained within the database. Rapid and accurate search of the vector space is carried out using exact search using metric data structures, or approximate search using locality sensitive hashing.

Abstract: Disclosed are methods, systems, and articles of manufacture for performing a process on biological samples. An analysis of biological samples in multiple regions of interest in a microfluidic device and a timeline correlated with the analysis may be identified. One or more region-of-interest types for the multiple regions of interest may be determined; and multiple characteristics may be determined for the biological samples based at least in part upon the one or more region-of-interest types. Associated data that respectively correspond to the multiple regions of interest in a user interface for at least a portion of the biological samples in the user interface based at least in part upon the multiple identifiers and the timeline. A count of the biological samples in a region of interest may be determined based at least in part upon a class or type of data using a convolutional neural network (CNN).

Abstract: A computer-implemented method for predicting a conformation of a ligand docked into a protein is disclosed. According to some embodiments, the method may include determining one or more poses of the ligand in the protein, the poses being representative conformations of the ligand. The method may also include determining, using a neural network, energy scores of the poses. The method may further include determining a proper conformation for the docked ligand based on the energy scores.

Abstract: Analysis of genetic disease progression may be provided. Data about a set of molecular status may be received. A dynamic prediction model of molecular interactions may be provided over time. The molecular statuses of the set over time may be determined using the dynamic prediction model. The determined molecular statuses may be clustered by applying an interaction-aware metric for the analysis of the genetic disease progression.

Abstract: The invention relates to an in silico screening method to identify candidate excipients for reducing aggregation of a protein in a formulation. The method combines computational molecular modeling and molecular dynamics simulations to identify sites on a protein where non-specific self-interaction and interaction of different test excipients may occur, determine the relative binding energies of such interactions, and select one or more test excipients that meet specified interaction criteria for use as candidate excipients in empirical screening studies.

Abstract: The present disclosure is directed to a computer-implemented method and system for anatomical tree structure analysis. The method includes receiving model inputs for a set of positions in an anatomical tree structure. The method further includes applying, by a processor, a set of encoders to the model inputs. Each encoder is configured to extract features from the model input at a corresponding position. The method also includes applying, by the processor, a tree structured network to the extracted features. The tree structured network has a plurality of nodes each connected to one or more of the encoders, and information propagates among the nodes of the tree structured network according to spatial constraints of the anatomical tree structure. The method additionally includes providing an output of the tree structured network as an analysis result of the anatomical tree structure analysis.

Abstract: The present disclosure provides methods and systems for identifying natural product-encoding multi-gene clusters (MGCs). In some embodiments, the present disclosure also teaches methods for producing sequenced and assembled metagenomic libraries that are amenable to MGC search bioinformatic tools and techniques.

Abstract: Disclosed herein are systems and methods for multiplex primer design and selection. In one example, a system includes non-transitory memory configured to store executable instructions; and a hardware processor programmed by the executable instructions to receive a plurality of target gene sequences and determine a set of primers for each target gene sequence based on a penalty score associated with the set of primers, wherein the penalty score is based on a non-linear combination of a primer-level penalty score and a set-level penalty score.

Abstract: Disclosed is a measurement method for measuring a test substance contained in a biological sample based on a predetermined measurement principle, comprising acquiring a first measured value of the test substance using a first measurement reagent, and operating the first measured value to an arithmetic value when measured using a second measurement reagent different from the first measurement reagent, by using arithmetic information designed to make a first cut-off value for the measured value obtained using the first measurement reagent correspond to a second cut-off value for a measured value obtained using the second measurement reagent.

Abstract: The present invention provides a process and method for repurposing existing compounds by leveraging genomic, phenotypic and pharmacological data to cure disease. Applying advanced mathematical analytics using massively interconnected computing capabilities to identify target rich sets of existing compounds available for animal testing at the earliest stage in the process collapses cycle time of development, dramatically reducing costs. Target rich sets obtained through this invention produce compounds or compositions which each have a demonstrated ability to modulate disease or an associated phenotypic expression. By rendering the mechanism of action irrelevant, this invention collapses the time and cost to discovery of an efficacious drug from decades to days and from $Billions to $Millions.