This invention relates to systems and methods for evaluating the differentiality of a set of discrete random variables between two or more conditions, such as a malignant condition responding to treatment regime and one that is not. It also provides for the identification and selection of drugs that act in coordinated manner to phenocopy a genetic network of a malignant condition that responds to at least an immune checkpoint blockade agent.

A computer-implemented method of preparing a set of differentially informative methylated positions (DIMPs) or differentially informative methylated regions (DIMRs) from a sample methylome of an animal or plant having a phenotypic characteristic different from a wild-type of the same species of animal or plant, and the characteristic is associate with differences in methylation of the genome, comprises: providing a computer with the sample methylome, and a reference methylome of the wild-type of the same species of animal or plant; calculating with the computer a divergence between a plurality of cytosine positions of the sample methylome and the reference methylome; and selecting with the computer a set of DIMPs or DIMRs. Each DIMP or DIMR is selected based on an approximation of the energy required to produce the divergence between methylation levels of the plurality of cytosine positions of the sample methylome as compared to the wild-type methylome.

The present invention provides systems, methods and software for improving robustness of transcriptomic data analysis, the method including receiving control cell transcriptomic data (C) and cell transcriptomic data (S) under study for a gene, calculating a fold change ratio (fc) for the gene, repeating these steps for a plurality of genes, grouping co-expressed genes into modules, estimating gene importance factors based on a network topology, mapped from a plurality of the modules and obtaining a insilico Pathway Activation Network Decomposition Analysis (iPANDA) value, wherein the iPANDA value has a Pearson coefficient greater than a Pearson coefficient associated with another platform for manipulating the same data.

A technique of using collaborative family medical history (CFMH) to estimate disease risk includes establishing CFMH information of a user and a plurality of relatives of the user, the CFMH information including genetic information of at least some of the family members, genetic information of the user, or both. It further includes analyzing the CFMH information, including the genetic information. It further includes determining a potential risk condition of the user and a potential risk condition of at least a family member based on the CFMH information. It also includes outputting the potential risk condition of the user and the potential risk condition of the at least one family member.

There are provided methods, systems and processes for the utilization of microbial and related genetic information for use in the exploration, determination, production and recovery of natural resources, including energy sources, and the monitoring, control and analysis of processes and activities.

A representation of a nucleic acid sequence encodes a particular gene having at least one intron. An intron signature value corresponding to the at least one intron is determined based on a first computational function applied to at least one portion of the representation of the nucleic acid sequence corresponding to the at least one intron. A protein signature value is determined, being based on a second computational function applied to a representation of a protein. In a database, an association is formed between the intron and protein signature values. This process is repeated for each of a plurality of nucleic acid sequences. Nucleic acid sequences in the database are ordered based on a sort of corresponding intron signature values. An ordering determined by the sort is used to determine or confirm a role or function of a portion of a given nucleic acid sequence.

Disclosed is a method of generating a set of sequence-verified nucleic acid elements for the combinatorial construction of genetic elements. The method includes: providing a plurality of nucleic acid parts; assembling nucleic acid parts to form a one or more nucleic acid elements, wherein the nucleic acid elements include at least two sequences selected from the plurality of parts; and determining the sequence of the nucleic acid elements. Further disclosed is pool of higher-order nucleic acid constructs or amplification products thereof, comprising one or more nucleic acid elements as well as kits including a the pool of sequence-verified nucleic acid elements of claims and/or a pool of higher-order nucleic acid constructs; and a plurality of primers for retrieving one or more sequence-verified nucleic acid elements and/or higher-order nucleic acid constructs.

Methods and systems for identifying causal genetic mechanisms of antibiotic resistance in pathogens. In accordance with at least one embodiment, the system includes a gene resistance module to identify genes present in an antibiotic resistant pathogen, a single nucleotide polymorphism module to identify mutations present in an antibiotic resistant pathogen, and an antibiotic resistance module configured to output the causation of antibiotic resistance based on the identified genes and mutations.

A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data is provided. Particularly, a genomics analysis platform for executing a sequence analysis pipeline is provided. The genomics analysis platform includes one or more of a first integrated circuit, where each first integrated circuit forms a central processing unit (CPU) that is responsive to one or more software algorithms that are configured to instruct the CPU to perform a first set of genomic processing steps of the sequence analysis pipeline. Additionally, a second integrated circuit is also provided, where each second integrated circuit forming a field programmable gate array (FPGA), the FPGA being configured by firmware to arrange a set of hardwired digital logic circuits that are interconnected by a plurality of physical interconnects to perform a second set of genomic processing steps of the sequence analysis pipeline, the set of hardwired digital logic circuits of each FPGA being arranged as a set of processing engines to perform the second set of genomic processing steps. A shared memory is also provided.

A method and system is provided for visualization and pictorial presentation to a user of possible interactions between a prospective drug that is being considered for prescribing to a person and that person's genotype. Genetic information of the person that can affect the manner in which a drug acts on a molecular, physiological or biological function of the body or a tissue, or a manner in which a drug is being metabolized, absorbed, excreted or otherwise eliminated from the body or a tissue by the body or tissue systems, is entered into a computerized device. The computerized device conducts a search of a drug database for drugs that have known interactions with the entered genetic information, and assigns a numeric value to each of a plurality of drugs, either in aggregate, as a class, or individually, in order to quantify the nature, strength and direction of each interaction. The computer sends the assigned numeric values to the computer's output module for their visual presentation to a user as a graph including a panel of columns, or other geometrical structures, whose geometrical characteristics correspond to the assigned numeric values of each drug, in order to facilitate the prospective drug selection by a prescriber on the basis of the totality of drug-gene and/or drug-drug interactions presented to the user as a visual graph.