95 results about "Protein network" patented technology

The invention relates to non-fermentation type sour milk and a preparation method thereof. The non-fermentation type sour milk uses fresh cow milk as principal raw material. After being hydrolyzed by milk sugar, the cow milk is pasteurized and concentrated in vacuum to be 40 percent of the original volume. After the cow milk is cooled, probiotic powder is added. The invention has the core that transglutaminase is added at an optimal temperature; under the action of the transglutaminase, milk protein is connected together to form a protein network, thereby a uniform stable gelatin system is easily formed; delta-gluconolactone is then added, and the gelatin system and the delta-gluconolactone are heated at 35-40 DEG C in a water bath way for 2 to 3 hours so that the uniform, stable and exquisite non-fermentation type sour milk like a quark can be obtained. The invention has simple preparing process, no requirement for fermentation, and full utilization of resources. The non-fermentation type sour milk can be used as a base to develop various products, such as corn non-fermentation type sour milk for breakfast, jelly non-fermentation type sour milk, and the like, and can satisfy the requirements of consumers in nutrition, mouthfeel, texture, and the like.

The invention relates to an instant cheese and a preparation method thereof. The preparation method comprises the steps: using full-cream fresh milk as main material, pasteurizing the milk after being hydrolyzed through lactase, and concentrating the full-cream fresh milk to 35-40 percent of the original volume in vacuum. The preparation method of the instant cheese has the core points that transglutaminase is added at 35 DEG C, and milk proteins are linked to form a protein network under the action of the transglutaminase, thereby forming a uniform and stable gel system easily. Then, chymosin is added for promoting gel to form , and uniform, stable and delicate instant cheese can be obtained in a water bath for half hour at about 30 DEG C. The invention is simple and easy for operation, and can be used for development of various application products on the theoretical basis, including breakfast cereal cheese, jelly cheese and the like. Moreover, the instant cheese can meet the requirements of consumers for taste, texture, nutrition, and the like.

The invention provides fibrin-based, biocompatible materials useful in promoting cell growth, wound healing, and tissue regeneration. These materials are provided as part of several cell and tissue scaffolding structures that provide particular application for use in wound-healing and tissue regenerating. Methods for preparing these compositions and using them are also disclosed as part of the invention. A variety of peptides may be used in conjunction with the practice of the invention, in particular, the peptide IKVAV, and variants thereof. Generally, the compositions may be described as comprising a protein network (e.g., fibrin) and a peptide having an amino acid sequence that comprises a transglutaminase substrate domain (e.g., a factor XIIIa substrate domain) and a bioactive factor (e.g., a peptide or protein, such as a polypeptide growth factor), the peptide being covalently bound to the protein network. Other applications of the technology include their use on implantable devices (e.g., vascular graphs), tissue and cell scaffolding. Other applications include use in surgical adhesive or sealant, as well as in peripheral nerve regeneration and angiogenesis.

Methods for producing biocompatible heterogeneous proteinaceous networks crosslinked with a heterogeneous crosslinking agent, and the novel crosslinked networks.

The present invention relates to a method for producing frozen dough by using ice-structure protein and utilizing a certain antifreezing fermentation process, belonging to the field of food processing technology. Said production method includes the following steps: adding wheat flour, granulated sugar, milk powder and yeast into a stirring apparatus, slowly beating and uniformly stirring them to obtain their mixture; dissolving ice-structure protein in ice water and adding them into the above-mentioned mixture, beating until the dough is formed into gluten film; adding salt and butter, beating them until the dough is formed into uniform and transparent film, taking out dough, standing still, cutting, rolling, further standing still, shaping and placing the dough into a refrigerator until the dough is completely hardened, sealing and storing; taking out frozen dough and proving so as to obtain the invented finished product.

The invention discloses a microRNA-disease association prediction method based on a multi-mode stacking automatic coding machine. The method comprises: forming microRNA sequence features and disease semantic similarity features; constructing a microRNA-protein-disease network, a microRNA-mRNA-disease network and a microRNA-lncRNA-disease network, and respectively obtaining network adjacent characteristics between microRNA and protein, between disease and protein, between mRNA and lncRNA and between disease and lncRNA by using a LINE network embedding method; mining, by using a multi-mode stacking automatic coding machine, the advanced abstract features of four features (self attribute features, protein network adjacent features, mRNA network adjacent features and lncRNA network adjacent features) of microRNA and diseases, thereby reducing the time complexity of a model and improving the prediction accuracy of the model; and training and predicting the processed features by using a CatBoost classifier, and taking an average value of prediction scores of the four features as a final prediction score. According to the method, the problems of high time consumption and high cost of a traditional biological experiment method are solved, so that a better classification effect is achieved, and the potential incidence relation between microRNA and diseases is predicted with higher accuracy.

The invention discloses an indeterminate PPI network function module mining method based on fuzzy spectral clustering. The method comprises the following steps: removing repeated interaction and self-interaction in protein-protein interaction data, measuring the interaction of each group by using an edge clustering coefficient, and constructing an indeterminate protein-protein interaction networkchart; improving the similarity measure of the spectral clustering algorithm by using popular distance and the topological properties of the protein network, and further adopting the spectral clustering algorithm to complete preprocessing on protein-protein interaction data; selecting an initial clustering center by using a DPCS strategy, based on the initial clustering center, using a fuzzy C-mean value algorithm to constantly update a clustering center and degree of membership, and then realizing the mining of a protein-protein interaction function module; filtering the mined protein-proteininteraction function module by using the edge expected density of an edge clustering coefficient fused by expected density; and outputting and predicting the mined protein-protein interaction function module.

A new fractionation device shows desirable features for exploratory screening and biomarker discovery. The constituent MSCs may be tailored for desired pore sizes and surface properties and for the sequestration and enrichment of extremely low abundant protein and peptides in desired ranges of the mass / charge spectrum. The MSCs are effective in yielding reproducible extracts from complex biological samples as small as 10 μl in a time as short as 30 minutes. They are inexpensive to manufacture, and allow for scaled up production to attain the simultaneous processing of a large number of samples. The MSCs are multiplexed, label-free diagnostic tools with the potential of biological recognition moiety modification for enhanced specificity. The MSCs may store, protect and stabilize biological fluids, enabling the simplified and cost-effective collection and transportation of clinical samples. The MSC-based device may serve as a diagnostic tool to complement histopathology, imaging, and other conventional clinical techniques. The MSCs mediated identification of disease-specific protein signatures may help in the selection of personalized therapeutic combinations, in the real-time assessment of therapeutic efficacy and toxicity, and in the rational modulation of therapy based on the changes in the protein networks associated with the prognosis and the drug resistance of the disease.

The invention discloses a monoclonal antibody of S-adenosylmethionine synthetase. A heavy chain variable region sequence of the monoclonal antibody contains CDR amino acid sequences shown by SEQ ID NO.2, 4 and 6; a light chain variable region sequence contains CDR amino acid sequences shown by SEQ ID NO.9, 11 and 13. The polypeptide of the enzyme is used as an immunogen for immunizing a mouse to obtain lymphocyte; a hybridoma fusion technology is used for preparing fusion cells; a cell strain capable of detecting and identifying the S-adenosylmethionine synthetase at high affinity and high specificity is obtained. The monoclonal antibody can be used for detecting the content of S-adenosylmethionine synthetase in bodies of animals and plants. The monoclonal antibody provides a targeted protein study tool, so that the deep level study of protein network atlas and the protein expression change on different plant types, different strains or different development periods can be realized.

The present invention relates to methods and compositions for the high throughput screening of protein-protein interactions in yeast liquid culture. Protein fusions non-native to yeast may be expressed to replace endogenous sexual agglutination proteins and mediate library-by-library interrogation of protein interactions. The methods and compositions of the invention can be utilized for the characterization of protein interaction networks in high throughput for both binding affinity and specificity, which is crucial for understanding cellular functions, screening therapeutic candidates, and evaluating engineered protein networks.