Evidence map›Paper›PMID 23155465›Full record

ArticlePloS one2012

Formalization, annotation and analysis of diverse drug and probe screening assay datasets using the BioAssay Ontology (BAO).

Uma D Vempati, Magdalena J Przydzial, Caty Chung, Saminda Abeyruwan, Ahsan Mir, Kunie Sakurai, Ubbo Visser, Vance P Lemmon, Stephan C Schürer

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Pooled it
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  13. ExtendingFrontiers in pharmacology · 2018
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  17. Badapple: promiscuity patterns from noisy evidence.Journal of cheminformatics · 2016
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  18. Database: A New Article Type in CPT: Pharmacometrics & Systems Pharmacology.CPT: pharmacometrics & systems pharmacology · 2015
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Uma D VempatiCenter for Computational Science, University of Miami, Miami, Florida, United States of America.
Magdalena J Przydzial
Caty Chung
Saminda Abeyruwan
Ahsan Mir
Kunie Sakurai
Ubbo Visser
Vance P Lemmon
Stephan C Schürer
University of Miami · US

Funding

Regenbase: A Searchable Database to Organize Regeneration Knowledge via OntologieR01NS080145 · NINDS · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI BIXBY, JOHN L, LEMMON, VANCE P · 2012 to 2015
$2.3M
Bioassay Ontology and Software Tools to Integrate and Analyze Diverse Data SetsRC2HG005668 · NHGRI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI LEMMON, VANCE P, SCHURER, STEPHAN C · 2009 to 2012
$1.7M
LINCS Information FramEwork (LIFE) to Integrate and Analyze Diverse Data SetU01HL111561 · NHLBI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI SCHURER, STEPHAN C · 2011 to 2013
$1.6M
NHGRI NIH HHS RC2 HG005668NHLBI NIH HHS U01 HL111561NINDS NIH HHS R01 NS080145
6 · The paper itself

Abstract

Huge amounts of high-throughput screening (HTS) data for probe and drug development projects are being generated in the pharmaceutical industry and more recently in the public sector. The resulting experimental datasets are increasingly being disseminated via publically accessible repositories. However, existing repositories lack sufficient metadata to describe the experiments and are often difficult to navigate by non-experts. The lack of standardized descriptions and semantics of biological assays and screening results hinder targeted data retrieval, integration, aggregation, and analyses across different HTS datasets, for example to infer mechanisms of action of small molecule perturbagens. To address these limitations, we created the BioAssay Ontology (BAO). BAO has been developed with a focus on data integration and analysis enabling the classification of assays and screening results by concepts that relate to format, assay design, technology, target, and endpoint. Previously, we reported on the higher-level design of BAO and on the semantic querying capabilities offered by the ontology-indexed triple store of HTS data. Here, we report on our detailed design, annotation pipeline, substantially enlarged annotation knowledgebase, and analysis results. We used BAO to annotate assays from the largest public HTS data repository, PubChem, and demonstrate its utility to categorize and analyze diverse HTS results from numerous experiments. BAO is publically available from the NCBO BioPortal at http://bioportal.bioontology.org/ontologies/1533. BAO provides controlled terminology and uniform scope to report probe and drug discovery screening assays and results. BAO leverages description logic to formalize the domain knowledge and facilitate the semantic integration with diverse other resources. As a consequence, BAO offers the potential to infer new knowledge from a corpus of assay results, for example molecular mechanisms of action of perturbagens.

Indexed as

Computational BiologyDatabases, FactualDrug Evaluation, PreclinicalHigh-Throughput Screening Assays

Identifiers

PMID23155465
PMCPMC3498356
OpenAlexW2049415080

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.