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公开(公告)号：US20190258776A1
公开(公告)日：2019-08-22
申请号：US15900048
申请日：2018-02-20
发明人： FILIPPO UTRO , ALDO GUZMAN SAENZ , CHAYA LEVOVITZ , LAXMI PARIDA
摘要： A computer-implemented method includes generating, by a processor, a set of training data for each phenotype in a database including a set of subjects. The set of training data is generated by dividing genomic information of N subjects selected with or without repetition into windows, computing a distribution of genomic events in the windows for each of N subjects, and extracting, for each window, a tensor that represents the distribution of genomic events for each of N subjects. A set of test data is generated for each phenotype in the database, a distribution of genomic events in windows for each phenotype is computed, and a tensor is extracted for each window that represents a distribution of genomic events for each phenotype. The method includes classifying each phenotype of the test data with a classifier, and assigning a phenotype to a patient.
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公开(公告)号：US20210005282A1
公开(公告)日：2021-01-07
申请号：US16459948
申请日：2019-07-02
IPC分类号： G16B25/10 , G16B20/00 , G16B30/00 , G16B25/20 , C12Q1/6869
摘要： A computer-implemented method includes to determine a cell, tissue or a lesion representation in cell-free DNA comprises inputting, to a processor, cell-free DNA (cfDNA) genomic profiles from one or more fluid biopsy samples from a patient and one or more genomic profiles from one or more cells, tissues or lesions from the patient; constructing, by the processor, a plurality of synthetic fluid hypotheses (SFs); comparing, by the processor, each of the plurality of SFs to the cfDNA genomic profiles to determine goodness of fit, of each of the plurality of SFs; selecting, by the processor, a subset of the plurality of SFs, wherein each SF of the subset of SFs has a minimum distance in goodness of fit compared to the cfDNA genomic profile; and outputting, by the processor, based on the subset of SFs, a cell, tissue or a lesion representation in the cfDNA of the patient.
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公开(公告)号：US20240038336A1
公开(公告)日：2024-02-01
申请号：US17814850
申请日：2022-07-26
摘要： A method is provided for training a predicting cfDNA shedding model using a plurality of lesion and cfDNA datasets. A new cfDNA shedding sample and the plurality of lesion and cfDNA datasets are clustered to predict a shedding pattern. A diagnostic type is determined for a subsequent cfDNA shedding sample based on the predicted shedding pattern.
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公开(公告)号：US20170169183A1
公开(公告)日：2017-06-15
申请号：US14968140
申请日：2015-12-14
CPC分类号： G06F19/3456 , G16B5/00 , G16B35/00 , G16C20/60
摘要： Embodiments are directed to a computer implemented method of assessing a relevancy of a drug to a disease state of a patient. The method includes assessing an impact of the drug on driver genes (DGs) of the disease state of the patient, assessing an impact of the drug on druggable target genes (DTs) of the drug, and assessing the relationship between the DGs and DTs that are in one of a plurality of biological pathways of the disease state of the patient. The method further includes combining the impact of the drug on the DGs, the impact of the drug on the DTs, and the relationship between the DGs and DTs that are in the one of the biological pathways, wherein the combining results in an assessment of the relevancy of the drug to the disease state of the patient.
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