Abstract: Systems and methods for determining radiation exposure during an x-ray guided medical procedure are disclosed. In some embodiments, the system includes an x-ray equipment model that simulates the emission of radiation from x-ray equipment during the x-ray guided medical procedure, a human exposure model that simulates one or more human anatomies during the x-ray guided medical procedure, a radiation metric processor that calculates at least one radiation exposure metric, and a feedback system for outputting information based on the at least one radiation exposure metric. The radiation metric processor calculates radiation exposure metrics based on input parameters that correspond to operating settings as well as the location and structure of one or more human anatomies.

Abstract: The invention provides a detection device, method, and program capable of highly accurately detecting a pre-disease state that indicates a precursor to a state transition from a healthy state to a disease state. The following processes are carried out: a process of obtaining measured data on genes, proteins, etc. related to a biological object as high-throughput data (s1), a process of selecting differential biological molecules (s2), a process of calculating the SNE of a local network (s3), a process of selecting a biomarker candidate (s4), a process of calculating an average SNE across the entire network (s5), and a process of determining and detecting whether or not the system is in a pre-disease state (s6).

Abstract: The present disclosure is directed to a computer-implemented method and system for anatomical tree structure analysis. The method may begin with receiving a task of the anatomical tree structure analysis. Then, a set of positions in the anatomical tree structure may be set or received, by a processor, as the sampling positions for model inputs and model outputs. Then model inputs may be determined, by the processor, at the sampling positions on the basis of the task. An encoder may be selected, by the processor, for each position of the set of positions on the basis of the task. The encoder may be configured to receive a model input at each position and extract features for the corresponding position. After that, a tree structured recurrent neural network (RNN) may be constructed by the processor with nodes corresponding to the set of positions and connected with the respective encoders.

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: Embodiments of the invention are directed to methods, systems and computer programs that provide improved risk stratification for people having elevated large HDL-P using at least one defined HDL risk interaction parameter.

Abstract: Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes or developing or having prediabetes using at least one defined mathematical model of risk of progression that can stratify risk for patients having the same glucose measurement. The model may include NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject.

Abstract: Provided is a variety identification-encoding system, including: a chromosome-decoding module decoding a chromosome of a reference genome variety and a chromosome of a target variety; a variation region-detecting module detecting a variation region in the decoded chromosome through single nucleotide variation dense region analysis; an amplification result-acquiring module setting an indel marker in the detected variation region and amplifying the indel marker by a polymerase chain reaction (PCR) to acquire an amplification result; and an encoding module encoding the amplification result.

Abstract: The present invention provides a method of a method of designing an implementation of a DNA assembly. In an exemplary embodiment, the method includes (1) receiving a list of DNA sequence fragments to be assembled together and an order in which to assemble the DNA sequence fragments, (2) designing DNA oligonucleotides (oligos) for each of the DNA sequence fragments, and (3) creating a plan for adding flanking homology sequences to each of the DNA oligos. In an exemplary embodiment, the method includes (1) receiving a list of DNA sequence fragments to be assembled together and an order in which to assemble the DNA sequence fragments, (2) designing DNA oligonucleotides (oligos) for each of the DNA sequence fragments, and (3) creating a plan for adding optimized overhang sequences to each of the DNA oligos.

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: Methods and devices use in two-color measurement systems. The methods and devices include methods of making corrections, methods of calculating correction factors, fluorescence scanners, and microarray chips. The said methods and devices enable a user to correct fluorescence intensities for errors caused by the occurrence of FRET and/or cross-talk when two fluorophores are used in two-color fluorescence arrays.

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 events by calculating a plurality of 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 method and system are provided for predicting chemical structures. The method includes receiving, at a user interface, intended structural feature values and intended chemical property values, as vectors. The method further includes constructing, by a hardware processor, a prediction model, wherein the prediction model predicts other structural feature values from the intended structural feature values and the intended chemical property values, and automatically configuring, by the hardware processor, at least one chemical structure candidate from the other structural feature vectors.

Abstract: In one embodiment, the disclosure relates to a method for conducting a spectral library search to identify an unknown compound by acquiring one or more spectra of the compound; representing each spectrum as a target vector; providing an n-dimensional space having a plurality of partitioned spaces, at least one of the partitioned spaces containing at least one known vector representing a known material; mapping each target vector in one of the plurality of the partitioned spaces to form a mapped partitioned space; identifying one or more known vectors within the mapped partitioned space which approximate the target vector; and identifying the unknown compound by comparing the target vector to the known vectors within the mapped partitioned space which closely approximate the target vector.

Abstract: A system and method of discovering sequence patterns with variations is provided. The method includes: accessing or acquiring a data set including a family of sequences or related families of sequences; a) applying a pattern discovery process to the sequences; b) grouping and aligning the similar patterns that may have different lengths into one or more Aligned Pattern Clusters; c) discovering the co-occurrence relation between Aligned Patterns and/or Aligned Pattern Clusters to reveal the distal function between segments represented by the aligned Pattern Clusters and d) breaking down an Aligned Pattern Cluster into sub-clusters with stable cluster configuration that reveals sub-clusters with distinct and shared characteristic among sub-family of the sequences.

Abstract: An system, and method are disclosed for harmonic modulation of standing wavefields for spatial focusing, manipulation, and patterning of particles, cells, powders, aerosols, colloids, and solids using a multifrequency wave source, a chamber a control module and an analysis module to generate standard wavefields useful for tissue engineering, micro fabrication, therapeutic treatment, and diagnostic tests.

Abstract: Systems and method for identifying variants associated with a genetic disease can include obtaining calls for a plurality of individuals for a list of variant positions. The calls can be compared to identify variants that are found in affected individuals and absent in non-affected individuals. Such variants can include loss of heterozygosity, trans-phased compound heterozygotes, increased frequency mitochondrial variants, homozygous recessive variants, de novo variants, sex-linked variants, and combinations thereof.

Abstract: Methods and systems are disclosed for encoding and decoding data from genetic traits. In one embodiment, the invention provides a method of encoding data from genetic traits. The method comprises encoding genetic traits information, including using quantum dot wavelengths to identify distinct genetic traits, and using numbers of the quantum dots to represent probabilities associated with the traits. In an embodiment, the invention provides a genetic characteristics decoding system for decoding genetic information encoded using quantum dots in a carrier. The decoding system comprises a light source for charging the quantum dots in the carrier; a scanner for scanning the carrier to retrieve information from the charged quantum dots; and a processing system for processing the retrieved information to determine quantum dot wavelengths to identify distinct genetic traits, and to determine numbers of the quantum dots to identify probabilities associated with the genetic traits.

Abstract: Provided are a method and apparatus for designing and processing a rule pipeline for in silico prediction of chemical reactions. The method includes designing a rule pipeline from at least one rule for chemical conversion and processing at least one input molecule by using the designed rule pipeline to predict a chemical reaction based on a processing result of the processing.

Abstract: According to the present invention, a phylogenetic tree can be created on the basis of frequency data regarding a large number of mutations detected from the samples of a cancer. Each sample to be analyzed contains a mixture of plural clones having different genomes. Mutations having about the same frequencies are grouped to make plural groups, and an analysis is executed based on data listing the mutation frequencies of individual groups (called mutation group frequency data). It is assumed that pairs of clones corresponding respectively to mutation groups such that frequencies of one group is equal to or greater than that of another in all the samples have parent-child relations, and a graph structure having the clones as vertices and the parent-child relations as edges is created.

Abstract: A device may receive information identifying results of a spectroscopic measurement of an unknown sample. The device may perform a first classification of the unknown sample based on the results of the spectroscopic measurement and a global classification model. The device may generate a local classification model based on the first classification. The device may perform a second classification of the unknown sample based on the results of the spectroscopic measurement and the local classification model. The device may provide information identifying a class associated with the unknown sample based on performing the second classification.