ArticleNucleic acids research2009
PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction.
Article in Nucleic acids research, 2009. 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.
- Review
- Large-scale structure of a network of co-occurring MeSH terms: statistical analysis of macroscopic properties.PloS one · 2014Article
- The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.The Plant cell · 2013Article
- PMRD: a curated database for genes and mutants involved in plant male reproduction.BMC plant biology · 2012Article
- Article
- Advances in omics and bioinformatics tools for systems analyses of plant functions.Plant & cell physiology · 2011Review
- BSQA: integrated text mining using entity relation semantics extracted from biological literature of insects.Nucleic acids research · 2010Article
- LAITOR--Literature Assistant for Identification of Terms co-Occurrences and Relationships.BMC bioinformatics · 2010Article
- Looking at cerebellar malformations through text-mined interactomes of mice and humans.PLoS computational biology · 2009Article
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
There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l.
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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.