Computer-implemented methods are provided for generating a personalized Boolean model for a genetic disease of a patient. The method includes storing specification data and reference model data. The reference model includes gene nodes, representing genes, connected to Boolean circuitry and a plurality of inputs for receiving binary input values. Each gene node in the reference model comprises a multiplexer. The multiplexer has a first input and an output, a second input for receiving a binary mutation value, and a control input for receiving a binary selector value. The method further comprises using a model checker to determine if the specification is reachable in the reference model. If the specification is reachable, the method includes identifying each multiplexer whose second input was connected to its output in the path reaching the specification to obtain mutation data for the patient, generating a personalized Boolean model, and outputting personal model data.

Computer-implemented methods are provided for generating a personalized Boolean model for a genetic disease of a patient. The method includes storing specification data and reference model data. The reference model includes gene nodes, representing genes, connected to Boolean circuitry and a plurality of inputs for receiving binary input values. Each gene node in the reference model comprises a multiplexer. The multiplexer has a first input and an output, a second input for receiving a binary mutation value, and a control input for receiving a binary selector value. The method further comprises using a model checker to determine if the specification is reachable in the reference model. If the specification is reachable, the method includes identifying each multiplexer whose second input was connected to its output in the path reaching the specification to obtain mutation data for the patient, generating a personalized Boolean model, and outputting personal model data.

Techniques for simulating networks using dynamics-based constraints are disclosed.

Disclosed herein are designed heterodimer proteins, monomeric polypeptides capable of forming heterodimer proteins, protein scaffolds including such polypeptides, and methods for using the heterodimer proteins and subunit polypeptides for designing logic gates.

Some embodiments disclosed herein provide a plurality of compositions each comprising a protein binding reagent conjugated with an oligonucleotide. The oligonucleotide comprises a unique identifier for the protein binding reagent it is conjugated with, and the protein binding reagent is capable of specifically binding to a protein target. Further disclosed are methods and kits for quantitative analysis of a plurality of protein targets in a sample and for simultaneous quantitative analysis of protein and nucleic acid targets in a sample. Also disclosed herein are systems and methods for preparing a labeled biomolecule reagent, including a labeled biomolecule agent comprising a protein binding reagent conjugated with an oligonucleotide.

Methods, systems, and software provide machine learning and artificial intelligence including deep neural networks that enable the creation and operation of unique, AI-driven genomic test results augmentation through variable genetic imputation.

Methods, systems, and software provide machine learning and artificial intelligence including deep neural networks that enable the creation and operation of unique, AI-driven genomic test results augmentation through variable genetic imputation.

The present invention relates to the filed of simulation of molecular interactions for assessing diseases and disease therapies. In particular, it relates to a system for simulating molecular interactions involved in inflammation in a subject, said system comprising a processing unit comprising a database comprising a plurality of datasets each comprising at least an identifier for a molecule suspected to be involved in the pathological process, data on molecular interactions of the said molecule with one or more other molecule, and at least one data characteristic that is allocated to the dataset, wherein each dataset has at least one relation with another dataset in the database based on molecular interactions, wherein the datasets are grouped into data compartments comprising datasets having identical data characteristics, and wherein the data characteristics are indicative for the biological function of a molecule in inflammation, and an computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map based on predefined parameters, and a visualization unit which allows for determination of the molecular interactions in the identified nodes. Moreover, the present invention contemplates a method for simulating molecular interactions involved in inflammation in a subject as well as the use of the system of the invention for simulating molecular interactions involved in inflammation.

The present invention relates to the filed of simulation of molecular interactions for assessing diseases and disease therapies. In particular, it relates to a system for simulating molecular interactions involved in inflammation in a subject, said system comprising a processing unit comprising a database comprising a plurality of datasets each comprising at least an identifier for a molecule suspected to be involved in the pathological process, data on molecular interactions of the said molecule with one or more other molecule, and at least one data characteristic that is allocated to the dataset, wherein each dataset has at least one relation with another dataset in the database based on molecular interactions, wherein the datasets are grouped into data compartments comprising datasets having identical data characteristics, and wherein the data characteristics are indicative for the biological function of a molecule in inflammation, and an computer program-based algorithm implemented in the processing unit which generates a network map based on the plurality of datasets in the database and which allows for identifying nodes within network map based on predefined parameters, and a visualization unit which allows for determination of the molecular interactions in the identified nodes. Moreover, the present invention contemplates a method for simulating molecular interactions involved in inflammation in a subject as well as the use of the system of the invention for simulating molecular interactions involved in inflammation.

Disclosed herein are designed heterodimer proteins, monomeric polypeptides capable of forming heterodimer proteins, protein scaffolds including such polypeptides, and methods for using the heterodimer proteins and subunit polypeptides for designing logic gates.