Patents by Inventor Monica Portela dos Santos Pimentel
Monica Portela dos Santos Pimentel has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20250104806Abstract: The present disclosure relates to an improved method for analyzing sequencing data to detect cross-sample contamination in a test sample. Determining cross-contamination in a test sample can be informative for determining that the test sample will be less likely to correctly identify the presence of cancer in the subject. Pre-determined single nucleotide polymorphisms selected from: an allele present in a select database or a genotyping SNP associated with a sample type are used to identify. A sample is determined to be contaminated using the determined contamination probabilities of the one or more pre-determined SNPs.Type: ApplicationFiled: January 27, 2023Publication date: March 27, 2025Inventors: Ruth Mauntz, Siddhartha Bagaria, David Burkhardt, Matthew H. Larson, Monica Portela dos Santos Pimentel
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Publication number: 20240249798Abstract: Systems and methods for determining a cancer class of a subject are provided in which a plurality of sequence reads, in electronic form, are obtained from a biological sample of the subject. The sample comprises a plurality of cell-free DNA molecules including respective DNA molecules longer than a threshold length of less than 160 nucleotides. The plurality of sequence reads excludes sequence reads of cell-free DNA molecules in the plurality of cell-free DNA molecules longer than the threshold length. The plurality of sequence reads is used to identify a relative copy number at each respective genomic location in a plurality of genomic locations in the genome of the subject. The genetic information about the subject obtained from the sample and the genetic information consisting of the identification of the relative copy number at each respective genomic location, is applied to a classifier that determines the cancer class of the subject.Type: ApplicationFiled: January 31, 2024Publication date: July 25, 2024Inventors: Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef
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Patent number: 11929148Abstract: Systems and methods for determining a cancer class of a subject are provided in which a plurality of sequence reads, in electronic form, are obtained from a biological sample of the subject. The sample comprises a plurality of cell-free DNA molecules including respective DNA molecules longer than a threshold length of less than 160 nucleotides. The plurality of sequence reads excludes sequence reads of cell-free DNA molecules in the plurality of cell-free DNA molecules longer than the threshold length. The plurality of sequence reads is used to identify a relative copy number at each respective genomic location in a plurality of genomic locations in the genome of the subject. The genetic information about the subject obtained from the sample and the genetic information consisting of the identification of the relative copy number at each respective genomic location, is applied to a classifier that determines the cancer class of the subject.Type: GrantFiled: March 12, 2020Date of Patent: March 12, 2024Assignee: GRAIL, LLCInventors: Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef
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Publication number: 20240062849Abstract: Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.Type: ApplicationFiled: August 31, 2023Publication date: February 22, 2024Applicant: GRAIL, LLCInventors: Virgil NICULA, Anton VALOUEV, Darya FILIPPOVA, Matthew H. LARSON, M. Cyrus MAHER, Monica Portela dos Santos Pimentel, Robert Abe Paine CALEF, Collin MELTON
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Patent number: 11783915Abstract: Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.Type: GrantFiled: September 29, 2022Date of Patent: October 10, 2023Assignee: GRAIL, LLCInventors: Virgil Nicula, Anton Valouev, Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef, Collin Melton
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Publication number: 20230045925Abstract: Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.Type: ApplicationFiled: September 29, 2022Publication date: February 16, 2023Applicant: GRAIL, LLCInventors: Virgil Nicula, Anton Valouev, Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef, Collin Melton
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Patent number: 11482303Abstract: Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.Type: GrantFiled: May 31, 2019Date of Patent: October 25, 2022Assignee: GRAIL, LLCInventors: Virgil Nicula, Anton Valouev, Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef, Collin Melton
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Publication number: 20200294624Abstract: Systems and methods for determining a cancer class of a subject are provided in which a plurality of sequence reads, in electronic form, are obtained from a biological sample of the subject. The sample comprises a plurality of cell-free DNA molecules including respective DNA molecules longer than a threshold length of less than 160 nucleotides. The plurality of sequence reads excludes sequence reads of cell-free DNA molecules in the plurality of cell-free DNA molecules longer than the threshold length. The plurality of sequence reads is used to identify a relative copy number at each respective genomic location in a plurality of genomic locations in the genome of the subject. The genetic information about the subject obtained from the sample and the genetic information consisting of the identification of the relative copy number at each respective genomic location, is applied to a classifier that determines the cancer class of the subject.Type: ApplicationFiled: March 12, 2020Publication date: September 17, 2020Inventors: Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef
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Publication number: 20200005899Abstract: Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.Type: ApplicationFiled: May 31, 2019Publication date: January 2, 2020Inventors: Virgil Nicula, Anton Valouev, Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef, Collin Melton
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Publication number: 20190287649Abstract: A system, method and computer program product for analyzing data of high dimensionality (e.g., sequence reads of nucleic acid samples in connection with a disease condition) are provided.Type: ApplicationFiled: March 13, 2019Publication date: September 19, 2019Inventors: Darya Filippova, Anton Valouev, Virgil Nicula, Karthik Jagadeesh, M. Cyrus Maher, Matthew H. Larson, Monica Portela dos Santos Pimentel, Robert Abe Paine Calef