Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology evaluates naturally occurring proteins by a process that is done partly in silico and partly by empirical evaluation. A database is created in which each individual protein is characterized by vector representations of structural and functional features. Clusters of individual proteins are formed by pairwise comparison of each protein's vector representation, adjusting the degree of similarity used to define clusters until a desired number of clusters are obtained. A protein representative is selected from each cluster for evaluation by high-throughput expression and laboratory testing for a particular food function. High scoring representatives identify clusters that can be mined for additional protein candidates. Multiple cycles of the machine learning, database mining, expression and testing yield ingredients suitable for assessment as part of a commercial food product.

Abstract: This disclosure provides a technology for developing individual proteins for use in industrial processes that include food production. The technology mines sequence data from protein databases by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for use in the production of foods, cosmetics, agricultural feed, pharmaceutical excipients, and other industrial products.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology mines sequence data by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression, and testing are done to yield potential ingredients suitable for assessment as part of a commercial food product.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology mines natural sources by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression and testing are done to yield potential ingredients suitable for assessment as part of a commercial food product.

Abstract: A system for high throughput foam analysis includes a foam generation system, an illumination source, a detection system and an analysis system. A foam generation system includes a first plurality of foaming units, each foaming unit including a foaming chamber and a gas induction mechanism. The illumination source provides an illumination to the foaming chamber of each foaming unit. The detection system includes a first camera configured to temporally record the foaming process in each foaming unit, thereby producing a first plurality of frames. The analysis system includes: at least one processor, and a memory including instructions for (i) obtaining a first respective frame in the first plurality of frames; (ii) segmenting the first respective frame into a first plurality of segmented images, and (iii) extracting, from each segmented image, one or more characteristics of the foam, thereby facilitating high throughput foam analysis of the first plurality of solutions.

Abstract: This disclosure provides a technology for developing alternative protein sources for use in industrial food production. The technology mines natural sources by a process that is done partly in silico. Instead of sampling and testing a vast library of compounds, machine learning and implementation narrows the field of functional candidates by predictive modeling based on known protein structure. Candidate proteins that are selected by this analysis are then produced and screened in a high-throughput manner by recombinant expression and testing to determine whether they have a target function. Multiple cycles of the machine learning, database mining, expression and testing are done to yield potential ingredients suitable for assessment as part of a commercial food product.

Abstract: A system for high throughput foam analysis includes a foam generation system, an illumination source, a detection system and an analysis system. A foam generation system includes a first plurality of foaming units, each foaming unit including a foaming chamber and a gas induction mechanism. The illumination source provides an illumination to the foaming chamber of each foaming unit. The detection system includes a first camera configured to temporally record the foaming process in each foaming unit, thereby producing a first plurality of frames. The analysis system includes: at least one processor, and a memory including instructions for (i) obtaining a first respective frame in the first plurality of frames; (ii) segmenting the first respective frame into a first plurality of segmented images, and (iii) extracting, from each segmented image, one or more characteristics of the foam, thereby facilitating high throughput foam analysis of the first plurality of solutions.

Abstract: A system for high throughput foam analysis includes a foam generation system, an illumination source, a detection system and an analysis system. A foam generation system includes a first plurality of foaming units, each foaming unit including a foaming chamber and a gas induction mechanism. The illumination source provides an illumination to the foaming chamber of each foaming unit. The detection system includes a first camera configured to temporally record the foaming process in each foaming unit, thereby producing a first plurality of frames. The analysis system includes: at least one processor, and a memory including instructions for (i) obtaining a first respective frame in the first plurality of frames; (ii) segmenting the first respective frame into a first plurality of segmented images, and (iii) extracting, from each segmented image, one or more characteristics of the foam, thereby facilitating high throughput foam analysis of the first plurality of solutions.

Abstract: A protein nanofiber comprised of self-assembling pentamers, and a method for producing the protein nanofiber, in which the protein upon which the nanofiber is based is a specific form of COMP. The proteins self-assemble via electrostatic interactions to form fibers that extend longitudinally.

Abstract: A protein nanofiber comprised of self-assembling pentamers, and a method for producing the protein nanofiber, in which the protein upon which the nanofiber is based is a specific form of COMP. The proteins self-assemble via electrostatic interactions to form fibers that extend longitudinally.