Compositions which are fragrant and contain at least a member set culled from a library of compositions, each being comprised of sub-combinations of selected terpenes. Fragrances that mimic that of various states of organic and synthetic aromatics including products, processes and those from non-combusted plant products, among other things, uniquitous products, processes, medicinals, and related moieties leverage databases of all known terpene groupings are offered for consideration, and have been provided, according to the instant teachings.

Disclosed herein are systems and methods for screening variant libraries for activity. Also disclosed herein are high throughput methods for identifying candidate variant having gain of function biological activity in an assay.

In traditional plant breeding approaches, chemical mutagenesis may be utilized to introduce nucleotide substitutions at random in the genome of a plant, i.e. without possibilities to control the sites of nucleotide changes. Because of genome complexities, the statistical probability is extremely little when it comes to finding a predetermined nucleotide substitution. The present invention, however, demonstrates how a novel, alternative use of digital polymerase chain reaction (dPCR), preferably droplet dPCR (ddPCR), is developed to exploit finding of specific nucleotide substitutions in mutated genes. The entire platform comprises a screening method with a library of mutagenized organisms, digital PCR-based systems and a set-up to propagate and analyze identified, mutated organisms.

A computer-implemented method and related system explore a combinatorial space. A combinatorial library and a desired output are identified. From the combinatorial library, an initial dataset is identified to be tested experimentally to create the combinatorial space. The following functions are iteratively performed: experimentally screening a set of diverse machine learning models (MLMs) using the initial data set or an augmented data set to produce experimental screening results; training the MLMs using the experimental screening results; selecting, from the MLMs, at least one MLM having a highest accuracy and performance; screening the combinatorial library; calculating a normalized similarity factor measured from top-ranked combinations; identifying, using the normalized similarity factor, an amount of the model-driven augmented data to be added to the top-ranked combinations; obtaining augmented data; and selecting the augmented data from the top-ranked combinations and the augmented combinatorial data. The iteration exits upon meeting an exit criterion.

A computer-implemented method and related system explore a combinatorial space. A combinatorial library and a desired output are identified. From the combinatorial library, an initial dataset is identified to be tested experimentally to create the combinatorial space. The following functions are iteratively performed: experimentally screening a set of diverse machine learning models (MLMs) using the initial data set or an augmented data set to produce experimental screening results; training the MLMs using the experimental screening results; selecting, from the MLMs, at least one MLM having a highest accuracy and performance; screening the combinatorial library; calculating a normalized similarity factor measured from top-ranked combinations; identifying, using the normalized similarity factor, an amount of the model-driven augmented data to be added to the top-ranked combinations; obtaining augmented data; and selecting the augmented data from the top-ranked combinations and the augmented combinatorial data. The iteration exits upon meeting an exit criterion.

A genetic prime editing screening platform to identify functional variants related to human health and disease, is configured substantially to annotate genome with nucleotide resolution with actionable disease prediction and treatment for personalized medicine.

A genetic prime editing screening platform to identify functional variants related to human health and disease, is configured substantially to annotate genome with nucleotide resolution with actionable disease prediction and treatment for personalized medicine.