ArticlePlant & cell physiology2016
HRGRN: A Graph Search-Empowered Integrative Database of Arabidopsis Signaling Transduction, Metabolism and Gene Regulation Networks.
Article in Plant & cell physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Bluster or Lustre: Can AI Improve Crops and Plant Health?Plants (Basel, Switzerland) · 2021Review
- An overview of graph databases and their applications in the biomedical domain.Database : the journal of biological databases and curation · 2021Article
- PhosPhAt 4.0: An Updated Arabidopsis Database for Searching Phosphorylation Sites and Kinase-Target Interactions.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Plant Regulomics Portal (PRP): a comprehensive integrated regulatory information and analysis portal for plant genomes.Database : the journal of biological databases and curation · 2019Article
- Network Modeling Unravels Mechanisms of Crosstalk between Ethylene and Salicylate Signaling in Potato.Plant physiology · 2018Article
- BED: a Biological Entity Dictionary based on a graph data model.F1000Research · 2018Article
- DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species.Scientific reports · 2017Article
- SeqEnrich: A tool to predict transcription factor networks from co-expressed Arabidopsis and Brassica napus gene sets.PloS one · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The biological networks controlling plant signal transduction, metabolism and gene regulation are composed of not only tens of thousands of genes, compounds, proteins and RNAs but also the complicated interactions and co-ordination among them. These networks play critical roles in many fundamental mechanisms, such as plant growth, development and environmental response. Although much is known about these complex interactions, the knowledge and data are currently scattered throughout the published literature, publicly available high-throughput data sets and third-party databases. Many 'unknown' yet important interactions among genes need to be mined and established through extensive computational analysis. However, exploring these complex biological interactions at the network level from existing heterogeneous resources remains challenging and time-consuming for biologists. Here, we introduce HRGRN, a graph search-empowered integrative database of Arabidopsis signal transduction, metabolism and gene regulatory networks. HRGRN utilizes Neo4j, which is a highly scalable graph database management system, to host large-scale biological interactions among genes, proteins, compounds and small RNAs that were either validated experimentally or predicted computationally. The associated biological pathway information was also specially marked for the interactions that are involved in the pathway to facilitate the investigation of cross-talk between pathways. Furthermore, HRGRN integrates a series of graph path search algorithms to discover novel relationships among genes, compounds, RNAs and even pathways from heterogeneous biological interaction data that could be missed by traditional SQL database search methods. Users can also build subnetworks based on known interactions. The outcomes are visualized with rich text, figures and interactive network graphs on web pages. The HRGRN database is freely available at http://plantgrn.noble.org/hrgrn/.
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.