Public articles linked to the same research event.
Journal of Agricultural and Food Chemistry This review surveys the diverse sources and novel preparation strategies of food-derived antihypertensive peptides, examines their multitarget mechanisms and structure-activity relationships, and summarizes how machine learning supports precise identification and activity prediction, arguing that future work should integrate advanced biotechnologies and intelligent platforms to accelerate the transition from laboratory to clinical application.
This review surveys the diverse sources and novel preparation strategies of food-derived antihypertensive peptides, examines their multitarget mechanisms and structure-activity relationships, and summarizes how machine learning supports precise identification and activity prediction, arguing that future work should integrate advanced biotechnologies and intelligent platforms to accelerate the transition from laboratory to clinical application.
This review surveys the diverse sources and novel preparation strategies of food-derived antihypertensive peptides, examines their multitarget mechanisms and structure-activity relationships, and summarizes how machine learning supports precise identification and activity prediction, arguing that future work should integrate advanced biotechnologies and intelligent platforms to accelerate the transition from laboratory to clinical application.
This review surveys the diverse sources and novel preparation strategies of food-derived antihypertensive peptides, examines their multitarget mechanisms and structure-activity relationships, and summarizes how machine learning supports precise identification and activity prediction, arguing that future work should integrate advanced biotechnologies and intelligent platforms to accelerate the transition from laboratory to clinical application.