A method for identifying by mass spectrometry an unknown microorganism subgroup among a set of reference subgroups, including a step of constructing one knowledgebase and one classifying model per associated subgroup on the basis of the acquisition of at least one set of learning spectra of microorganisms identified as belonging to the subgroups of a group and including: constructing an adjusting model allowing mass-to-charge offsets of the acquired spectra to be corrected on the basis of reference masses-to-charges that are common to the various subgroups; adjusting the masses-to-charges of all of the lists of peaks of the learning spectra and constructing one classifying model per subgroup and the associated knowledgebase on the basis of the adjusted learning spectra.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

The present disclosure provides an automated method of producing viral vectors, utilizing engineered viral vector-producing cell lines, or packaging cells, within a fully-enclosed cell engineering system. Exemplary viral vectors that can be produced include lentivirus vectors, adeno-associated virus vectors, baculovirus vectors and retrovirus vectors.

The present disclosure provides an automated method of producing viral vectors, utilizing engineered viral vector-producing cell lines, or packaging cells, within a fully-enclosed cell engineering system. Exemplary viral vectors that can be produced include lentivirus vectors, adeno-associated virus vectors, baculovirus vectors and retrovirus vectors.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.

A method for verifying a material data chain (MDC) that is maintained by a creator is disclosed. The method includes receiving an unverified portion of the MDC from the creator including a set of consecutive material data blocks (MDBs). Each respective MDB includes respective material data, respective metadata, and a creator verification value. The method includes modifying a genomic differentiation object assigned to the verification cohort based on first genomic regulation instructions (GRI) that were used by the creator to generate the creator verification value. For each MDB in the unverified portion, the method includes determining a verifier verification value based on the MDB, a preceding MDB in the MDC, and a genomic engagement factor (GEF) determined with respect to the MDB. The GEF corresponding to an MDB is determined by extracting a sequence from the metadata of a MDB and mapping the sequence into the modified genomic differentiation object.

A method for verifying a material data chain (MDC) that is maintained by a creator is disclosed. The method includes receiving an unverified portion of the MDC from the creator including a set of consecutive material data blocks (MDBs). Each respective MDB includes respective material data, respective metadata, and a creator verification value. The method includes modifying a genomic differentiation object assigned to the verification cohort based on first genomic regulation instructions (GRI) that were used by the creator to generate the creator verification value. For each MDB in the unverified portion, the method includes determining a verifier verification value based on the MDB, a preceding MDB in the MDC, and a genomic engagement factor (GEF) determined with respect to the MDB. The GEF corresponding to an MDB is determined by extracting a sequence from the metadata of a MDB and mapping the sequence into the modified genomic differentiation object.

This disclosure provides systems and methods for sample processing and data analysis. Sample processing may include nucleic acid sample processing and subsequent sequencing. Some or all of a nucleic acid sample may be sequenced to provide sequence information, which may be stored or otherwise maintained in an electronic storage location. The sequence information may be analyzed with the aid of a computer processor, and the analyzed sequence information may be stored in an electronic storage location that may include a pool or collection of sequence information and analyzed sequence information generated from the nucleic acid sample. Methods and systems of the present disclosure can be used, for example, for the analysis of a nucleic acid sample, for producing one or more libraries, and for producing biomedical reports. Methods and systems of the disclosure can aid in the diagnosis, monitoring, treatment, and prevention of one or more diseases and conditions.