ArticleAmerican journal of physiology. Renal physiology2014
A knowledge base of vasopressin actions in the kidney.
Article in American journal of physiology. Renal physiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Utilizing Omic Data to Understand Integrative Physiology.Physiology (Bethesda, Md.) · 2025Review
- Collecting duct water permeability inhibition by EGF is associated with decreased cAMP, PKA activity, and AQP2 phosphorylation at SerAmerican journal of physiology. Renal physiology · 2024Article
- Systems Biology of the Vasopressin V2 Receptor: New Tools for Discovery of Molecular Actions of a GPCR.Annual review of pharmacology and toxicology · 2022Review
- Chromatin accessibility associates with protein-RNA correlation in human cancer.Nature communications · 2021Observational
- From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes.American journal of physiology. Renal physiology · 2017Article
- Proteomic profiling of nuclear fractions from native renal inner medullary collecting duct cells.Physiological genomics · 2016Article
- Deep proteomic profiling of vasopressin-sensitive collecting duct cells. II. Bioinformatic analysis of vasopressin signaling.American journal of physiology. Cell physiology · 2015Article
- Inhibition of ENaC by endothelin-1.Vitamins and hormones · 2015Review
- Database of osmoregulated proteins in mammalian cells.Physiological reports · 2014Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.