A method is presented for analyzing interactions in a human genome. The method includes: receiving a biological sample of a cell from a subject; extracting read data from the biological sample, where the read data includes a set of reads; and constructing, by a computer processor, a hypergraph from the read data, where each node in the hypergraph represents a locus and hyperedges in the hypergraph represent interactions between two or more loci. The hypergraphs may be used for different applications including determining entropy, comparing different biological samples and reporting multi-way contacts in a set of transcription clusters.

The present invention relates to improved strategies, compositions, and methods for producing shared neoplasia vaccines, including “off the shelf” pre-furnished shared neo-epitope warehouses, which can be used to enable the rapid production of bladder cancer neoantigen-based vaccines. The present invention relates to identified and designed shared neo-epitopes based on non-synonymous mutations that are present in at least 1% of subjects having bladder cancer. The strategies, compositions, and methods include the identification of neo-epitopes that are known or determined (e.g. predicted) to engage regulatory T cells and/or other detrimental T cells (including T cells with potential host cross-reactivity and/or anergic T cells) and exclusion of such identified neo-epitopes that are known or determined (e.g. predicted) to engage regulatory T cells and/or other detrimental T cells (including T cells with potential host cross-reactivity and/or anergic T cells) from the shared neo-epitopes that are to be used in the shared neoantigen-based vaccines.

Amino acid sequences of antibodies can be generated using a generative adversarial network that includes a first generating component that generates amino acid sequences of antibody light chains and a second generating component generates amino acid sequences of antibody heavy chains. Amino acid sequences of antibodies can be produced by combining the respective amino acid sequences produced by the first generating component and the second generating component. The training of the first generating component and the second generating component can proceed at different rates. Additionally, the antibody amino acids produced by combining amino acid sequences from the first generating component and the second generating component may be evaluated according to complentarity-determining regions of the antibody amino acid sequences. Training datasets may be produced using amino acid sequences that correspond to antibodies have particular binding affinities with respect to molecules, such as binding affinity with major histocompatibility complex (MHC) molecules.

Amino acid sequences of antibodies can be generated using a generative adversarial network that includes a first generating component that generates amino acid sequences of antibody light chains and a second generating component generates amino acid sequences of antibody heavy chains. Amino acid sequences of antibodies can be produced by combining the respective amino acid sequences produced by the first generating component and the second generating component. The training of the first generating component and the second generating component can proceed at different rates. Additionally, the antibody amino acids produced by combining amino acid sequences from the first generating component and the second generating component may be evaluated according to complentarity-determining regions of the antibody amino acid sequences. Training datasets may be produced using amino acid sequences that correspond to antibodies have particular binding affinities with respect to molecules, such as binding affinity with major histocompatibility complex (MHC) molecules.

Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.

Disclosed herein are methods and systems of utilizing sequencing reads for detecting and quantifying the presence of a tissue type or a disease type in cell-free DNA prepared from blood samples.

The invention provides computational methods for engineering, selecting, and/or identifying proteins with a desired activity. Further provided are automated computational design and screening methods to engineer proteins with desired functional activities including, but not limited to ligand binding, catalytic activity, substrate specificity, regioselectivity and/or stereoselectivity.

The invention provides computational methods for engineering, selecting, and/or identifying proteins with a desired activity. Further provided are automated computational design and screening methods to engineer proteins with desired functional activities including, but not limited to ligand binding, catalytic activity, substrate specificity, regioselectivity and/or stereoselectivity.

A system for selecting an immunogenic peptide composition comprising a processor and a memory storing processor-executable instructions that, when executed by the processor, cause the processor to create a first peptide set by selecting a plurality of base peptides, wherein at least one peptide of the plurality of base peptides is associated with a disease, create a second peptide set by adding to the first peptide set a modified peptide, wherein the modified peptide comprises a substitution of at least one residue of a base peptide selected from the plurality of base peptides, and create a third peptide set by selecting a subset of the second peptide set, wherein the selected subset of the second peptide set has a predicted vaccine performance, wherein the predicted vaccine performance has a population coverage above a predetermined threshold, and wherein the subset comprises at least one peptide of the second peptide set.

A system for selecting an immunogenic peptide composition comprising a processor and a memory storing processor-executable instructions that, when executed by the processor, cause the processor to create a first peptide set by selecting a plurality of base peptides, wherein at least one peptide of the plurality of base peptides is associated with a disease, create a second peptide set by adding to the first peptide set a modified peptide, wherein the modified peptide comprises a substitution of at least one residue of a base peptide selected from the plurality of base peptides, and create a third peptide set by selecting a subset of the second peptide set, wherein the selected subset of the second peptide set has a predicted vaccine performance, wherein the predicted vaccine performance has a population coverage above a predetermined threshold, and wherein the subset comprises at least one peptide of the second peptide set.