Disclosed are compositions and methods relating to sequence-controlled storage objected. The disclosed sequence-controlled storage objects can include (a) one or more different sequence-controlled polymers, and (b) a plurality of different feature tags. The sequence-controlled storage object can include (a) one or more different sequence-controlled polymers, and (b) a plurality of different digit tags. Also disclosed are methods of storing desired sequence-controlled polymers as a sequence-controlled storage object, comprising assembling a sequence-controlled storage object from (i) one or more different sequence-controlled polymers, (ii) a plurality of different feature tags, and (iii) optionally one or more encapsulating agents. Also disclosed are methods of automating the assembly of a sequence-controlled storage object comprising using a device with flow.

Molecular computer techniques for solving a computational problem using an array of reaction sites, for example, droplets, are disclosed. The problem may be represented as a Hamiltonian in terms of problem variables and problem parameters. The reaction sites may have a physicochemical property mapping to discrete site states corresponding to possible values of the problem variables. In a purely molecular approach, the reaction sites have intra-site and inter-site couplings enforced thereon representing the problem parameters, and the array is allowed to evolve, subjected to the enforced couplings, to a final configuration conveying a solution to the problem. In a hybrid classical-molecular approach, an iterative procedure may be performed that involves feeding read-out site states into a digital computer, determining, based on the problem parameters, perturbations to be applied to the states, and allowing the array to evolve under the perturbations to a final configuration conveying a solution to the problem.

Systems, methods, and apparatuses for generating and using machine learning models using genetic data. A set of input features for training the machine learning model can be identified and used to train the model based on training samples, e.g., for which one or more labels are known. As examples, the input features can include aligned variables (e.g., derived from sequences aligned to a population level or individual references) and/or non-aligned variables (e.g., sequence content). The features can be classified into different groups based on the underlying genetic data or intermediate values resulting from a processing of the underlying genetic data. Features can be selected from a feature space for creating a feature vector for training a model. The selection and creation of feature vectors can be performed iteratively to train many models as part of a search for optimal features and an optimal model.

Provided herein are compositions, devices, systems and methods for the generation and use of biomolecule-based information for storage. Additionally, devices described herein for de novo synthesis of nucleic acids encoding information related to the original source information may be rigid or flexible material. Further described herein are highly efficient methods for long term data storage with 100% accuracy in the retention of information. Also provided herein are methods and systems for efficient transfer of preselected polynucleotides from a storage structure for reading stored information.

The present disclosure provides a method for screening cells, the method including a step of preparing a plurality of cells which are tagged with a first barcode nucleic acid associated with a test target and treated with the test target, a step of sorting the plurality of cells based on cellular phenotype using an imaging cell sorter, and a step of identifying the test target used to treat each cell using the first barcode nucleic acid as an indicator.

Disclosed are methods for identifying bio-molecules with desired properties (or which are most suitable for a round of directed evolution) from complex bio-molecule libraries or sets of such libraries. Some embodiments of the present disclosure provide methods for virtually screening proteins for beneficial properties. Some embodiments of the present disclosure provide methods for virtually screening enzymes for desired activity and/or selectivity for catalytic reactions involving particular substrates. Some embodiments combine screening and directed evolution to design and develop proteins and enzymes having desired properties. Systems and computer program products implementing the methods are also provided.

Embodiments of a method and system for improved microbiome sequencing can include: generating guide RNA complexes for a set of targets corresponding to a set of taxa associated with the microorganism-related condition; processing the biological sample with the gRNA complexes to generate microorganism nucleic acid fragments comprising a set of end regions associated with the set of targets; ligating the set of end regions with a set of adapters sharing an adapter sequence; and amplifying the set of targets based on the ligated set of end regions and a set of primers sharing a primer sequence associated with the adapter sequence.

Embodiments of a method and system for improved microbiome sequencing can include: generating guide RNA complexes for a set of targets corresponding to a set of taxa associated with the microorganism-related condition; processing the biological sample with the gRNA complexes to generate microorganism nucleic acid fragments comprising a set of end regions associated with the set of targets; ligating the set of end regions with a set of adapters sharing an adapter sequence; and amplifying the set of targets based on the ligated set of end regions and a set of primers sharing a primer sequence associated with the adapter sequence.

A method includes receiving measured activity from a first assay, the first assay comprising wells containing compounds and first controls. The measured activity may be indicative of activation or inhibition by the compounds on a process. The method includes determining an estimate of activity percentages of the compounds. The estimate of the activity percentages of the compounds may be based on a noise distribution, and the noise distribution may be based on the first controls. The method includes receiving a first reference based on a required activity percentage of compounds for the first assay. The method includes receiving a second reference based on a required accuracy percentage of the compounds identified as active according to the first reference. The method includes identifying active compounds of the first assay based on the first reference, the second reference, the measured activity, and the estimate of activity percentages.

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.