ArticleAmerican journal of physiology. Renal physiology2016
BIG: a large-scale data integration tool for renal physiology.
Article in American journal of physiology. Renal physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- Dehydration promotes intracellular lipid synthesis and accumulation.Nature communications · 2026Article
- Utilizing Omic Data to Understand Integrative Physiology.Physiology (Bethesda, Md.) · 2025Review
- Modulation of blood pressure regulatory genes in the Agtrap-Plod1 locus associated with a deletion in Clcn6.Physiological reports · 2022Article
- Systems Biology of the Vasopressin V2 Receptor: New Tools for Discovery of Molecular Actions of a GPCR.Annual review of pharmacology and toxicology · 2022Review
- Bayesian identification of candidate transcription factors for the regulation ofAmerican journal of physiology. Renal physiology · 2021Article
- From Molecules to Mechanisms: Functional Proteomics and Its Application to Renal Tubule Physiology.Physiological reviews · 2018Review
- How Omics Data Can Be Used in Nephrology.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2018Review
- Epithelial NaFrontiers in physiology · 2018Article
- Systems-level identification of PKA-dependent signaling in epithelial cells.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Identification of β-catenin-interacting proteins in nuclear fractions of native rat collecting duct cells.American journal of physiology. Renal physiology · 2017Article
- From 20th century metabolic wall charts to 21st century systems biology: database of mammalian metabolic enzymes.American journal of physiology. Renal physiology · 2017Article
- Data integration in physiology using Bayes' rule and minimum Bayes' factors: deubiquitylating enzymes in the renal collecting duct.Physiological genomics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: "How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?" This is the type of problem that has motivated the "Big-Data" revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.
Indexed as
Identifiers
What OpenQuestion holds
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.