ArticleBioinformatics and biology insights2013
On Crowd-verification of Biological Networks.
Article in Bioinformatics and biology insights, 2013. 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
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
9 citing papers in PubMed.
- The extraction of complex relationships and their conversion to biological expression language (BEL) overview of the BioCreative VI (2017) BEL track.Database : the journal of biological databases and curation · 2019Article
- Crowdsourcing biomedical research: leveraging communities as innovation engines.Nature reviews. Genetics · 2016Review
- Taking Bioinformatics to Systems Medicine.Methods in molecular biology (Clifton, N.J.) · 2016Review
- Training and evaluation corpora for the extraction of causal relationships encoded in biological expression language (BEL).Database : the journal of biological databases and curation · 2016Article
- Enhancement of COPD biological networks using a web-based collaboration interface.F1000Research · 2015Article
- Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.Database : the journal of biological databases and curation · 2015Article
- Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014Review
- Quantification of biological network perturbations for mechanistic insight and diagnostics using two-layer causal models.BMC bioinformatics · 2014Article
- Systems toxicology: from basic research to risk assessment.Chemical research in toxicology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community.
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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.