Processes and materials to detect cancer from a biopsy are described. In some cases, cell-free nucleic acids can be sequenced, and the sequencing result can be utilized to detect sequences derived from a neoplasm. Detection of somatic variants occurring in phase can indicate the presence of cancer in a diagnostic scan and a clinical intervention can be performed.

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.

A computer based biological sequence analysis method provides, after a training phase adopting data from screening experiments, either an evaluation of an input sequence expressing the performance with reference to the chemical-physical feature object of the screening experiment, or at least an optimized output sequence. The method provides the use of a set or library of sequences derived from DMS experiments and SELEX for the generation of a second set of high efficiency biological sequences, whereby high efficiency means, for example, high catalysis capacity, high fitness, high ability to bind to a specific target, high fluorescence activity and, in general, a high performance with reference to the chemical-physical properties of a molecule which are defined at the start and can be selected through experiments.

A computer based biological sequence analysis method provides, after a training phase adopting data from screening experiments, either an evaluation of an input sequence expressing the performance with reference to the chemical-physical feature object of the screening experiment, or at least an optimized output sequence. The method provides the use of a set or library of sequences derived from DMS experiments and SELEX for the generation of a second set of high efficiency biological sequences, whereby high efficiency means, for example, high catalysis capacity, high fitness, high ability to bind to a specific target, high fluorescence activity and, in general, a high performance with reference to the chemical-physical properties of a molecule which are defined at the start and can be selected through experiments.

Disclosed herein is an amplicon design workflow for improving the design of amplicons such that panels including newly designed amplicons can achieve improved performance (e.g., improved panel uniformity). The amplicon design workflow involves performing a feature selection process to identify key amplicon attributes that likely lead to improved amplicon performance. Therefore, improved amplicons can be designed based on these key attributes. A sequencing panel, such as a DNA sequencing panel or RNA sequencing panel can be constructed using these improved amplicons and further validated. Thus, such panels including improved amplicons can be deployed for analyzing single cells e.g., through a single cell workflow analysis, for characterizing the cells for nucleic acid events, such as the presence or absence of RNA fusion transcripts.

Disclosed herein is an amplicon design workflow for improving the design of amplicons such that panels including newly designed amplicons can achieve improved performance (e.g., improved panel uniformity). The amplicon design workflow involves performing a feature selection process to identify key amplicon attributes that likely lead to improved amplicon performance. Therefore, improved amplicons can be designed based on these key attributes. A sequencing panel, such as a DNA sequencing panel or RNA sequencing panel can be constructed using these improved amplicons and further validated. Thus, such panels including improved amplicons can be deployed for analyzing single cells e.g., through a single cell workflow analysis, for characterizing the cells for nucleic acid events, such as the presence or absence of RNA fusion transcripts.

Provided herein are automated apparatus and methods for the identification of microorganisms in various samples. The disclosure solves existing challenges encountered in identifying and distinguishing various types of microorganisms, including viruses and bacteria in a timely, efficient, and automated manner by library preparation and sequencing.

Provided herein are automated apparatus and methods for the identification of microorganisms in various samples. The disclosure solves existing challenges encountered in identifying and distinguishing various types of microorganisms, including viruses and bacteria in a timely, efficient, and automated manner by library preparation and sequencing.

The present disclosure provides a method for identifying a specific region in a microorganism target fragment, including the following operations: S100, respectively comparing a microorganism target fragment with genome sequences of one or more comparison strain one-to-one, and removing fragments of which the similarity exceeds a preset value, to obtain a plurality of residual fragments as first-round cut fragments T.sub.1-T.sub.n; S200, respectively comparing the first-round cut fragments T.sub.1-T.sub.n with the remaining comparison strains, and removing fragments of which the similarity exceeds a preset value, to obtain a collection of residual cut fragments as a candidate specific region of the microorganism target fragment; and S300, verifying and obtaining a specific region. The method is high in accuracy and sensitivity which can identify the subspecies level and a dual-verification module is provided. The present disclosure is suitable for identifying a specific region in the whole genome of any pathogen.

The present disclosure provides a method for identifying a specific region in a microorganism target fragment, including the following operations: S100, respectively comparing a microorganism target fragment with genome sequences of one or more comparison strain one-to-one, and removing fragments of which the similarity exceeds a preset value, to obtain a plurality of residual fragments as first-round cut fragments T.sub.1-T.sub.n; S200, respectively comparing the first-round cut fragments T.sub.1-T.sub.n with the remaining comparison strains, and removing fragments of which the similarity exceeds a preset value, to obtain a collection of residual cut fragments as a candidate specific region of the microorganism target fragment; and S300, verifying and obtaining a specific region. The method is high in accuracy and sensitivity which can identify the subspecies level and a dual-verification module is provided. The present disclosure is suitable for identifying a specific region in the whole genome of any pathogen.