ArticlePLoS computational biology2009
Looking at cerebellar malformations through text-mined interactomes of mice and humans.
Article in PLoS computational biology, 2009. 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.
- Automatic extraction of protein-protein interactions using grammatical relationship graph.BMC medical informatics and decision making · 2018Article
- Survey of Natural Language Processing Techniques in Bioinformatics.Computational and mathematical methods in medicine · 2015Review
- Text mining and network analysis of molecular interaction in non-small cell lung cancer by using natural language processing.Molecular biology reports · 2014Article
- Finding pathway-modulating genes from a novel Ontology Fingerprint-derived gene network.Nucleic acids research · 2014Article
- Network-based analysis of genome wide association data provides novel candidate genes for lipid and lipoprotein traits.Molecular & cellular proteomics : MCP · 2013Article
- Representation of probabilistic scientific knowledge.Journal of biomedical semantics · 2013Article
- Mining the pharmacogenomics literature--a survey of the state of the art.Briefings in bioinformatics · 2012Article
- Article
- Large-scale de novo prediction of physical protein-protein association.Molecular & cellular proteomics : MCP · 2011Article
- Article
- Article
- Recent progress in automatically extracting information from the pharmacogenomic literature.Pharmacogenomics · 2010Review
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.
Funding
Abstract
We have generated and made publicly available two very large networks of molecular interactions: 49,493 mouse-specific and 52,518 human-specific interactions. These networks were generated through automated analysis of 368,331 full-text research articles and 8,039,972 article abstracts from the PubMed database, using the GeneWays system. Our networks cover a wide spectrum of molecular interactions, such as bind, phosphorylate, glycosylate, and activate; 207 of these interaction types occur more than 1,000 times in our unfiltered, multi-species data set. Because mouse and human genes are linked through an orthological relationship, human and mouse networks are amenable to straightforward, joint computational analysis. Using our newly generated networks and known associations between mouse genes and cerebellar malformation phenotypes, we predicted a number of new associations between genes and five cerebellar phenotypes (small cerebellum, absent cerebellum, cerebellar degeneration, abnormal foliation, and abnormal vermis). Using a battery of statistical tests, we showed that genes that are associated with cerebellar phenotypes tend to form compact network clusters. Further, we observed that cerebellar malformation phenotypes tend to be associated with highly connected genes. This tendency was stronger for developmental phenotypes and weaker for cerebellar degeneration.
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.