ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2008
Gene-L'EXPO: a tool to extract knowledge From transcriptomes and find 'Literature-Sparse' relationships between genes and tissues.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing volume and diversity of transcriptome data in the public domain offer an opportunity to advance new questions and hypotheses. We anticipate that tools that can visualize the gap in the distribution of information between the scientific literature and actual data would prompt such questions. We focused on the roles played by various genes in tissues, and have developed a database that contrasts information on gene expression in tissues with PubMed text and transcriptome data. Data pairs of tissues and the genes that might be expressed there were automatically extracted from text with vocabularies for the genes and tissues. The anatomical categories of various expressed sequence tag (EST) libraries were also automatically determined. These types of information were linked using the hierarchical structure of the Metathesaurus in UMLS.
Indexed as
Identifiers
18999036PMC2656066What 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.