title: A knowledge base of vasopressin actions in the kidney.
abstract: Biological information is growing at a rapid pace, making it difficult for individual investigators to be familiar with all information that is relevant to their own research. Computers are beginning to be used to extract and curate biological information; however, the complexity of human language used in research papers continues to be a critical barrier to full automation of knowledge extraction. Here, we report a manually curated knowledge base of vasopressin actions in renal epithelial cells that is designed to be readable either by humans or by computer programs using natural language processing algorithms. The knowledge base consists of three related databases accessible at https://helixweb.nih.gov/ESBL/TinyUrls/Vaso_portal.html. One of the component databases reports vasopressin actions on individual proteins expressed in renal epithelia, including effects on phosphorylation, protein abundances, protein translocation from one subcellular compartment to another, protein-protein binding interactions, etc. The second database reports vasopressin actions on physiological measures in renal epithelia, and the third reports specific mRNA species whose abundances change in response to vasopressin. We illustrate the application of the knowledge base by using it to generate a protein kinase network that connects vasopressin binding in collecting duct cells to physiological effects to regulate the water channel protein aquaporin-2.
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland;
authors: Akshay
authors: A
authors: Sanghi
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland;
authors: Matthew
authors: M
authors: Zaringhalam
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland;
authors: Callan C
authors: CC
authors: Corcoran
authors: Departments of Electrical and Computer Engineering and Computer Science, Western Michigan University, Kalamazoo, Michigan.
authors: Fahad
authors: F
authors: Saeed
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland;
authors: Jason D
authors: JD
authors: Hoffert
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland;
authors: Pablo
authors: P
authors: Sandoval
authors: Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; and.
authors: Trairak
authors: T
authors: Pisitkun
authors: Epithelial Systems Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland; knep@helix.nih.gov.
authors: Mark A
authors: MA
authors: Knepper
mesh_terms: D000818:Animals; D001127:Arginine Vasopressin / Q000502:physiology*; D016208:Databases, Factual; D006801:Humans; D007668:Kidney / Q000502:physiology*; D051188:Knowledge Bases
chemical_list: D001127:Arginine Vasopressin
keywords: ENaC; aquaporin-2; database; urea channel