Evidence map›Paper›PMID 20646315›Full record

ArticleBMC bioinformatics2010

S3DB core: a framework for RDF generation and management in bioinformatics infrastructures.

Jonas S Almeida, Helena F Deus, Wolfgang Maass

Abstract read
In one paragraph

Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. epiDonate - distributed serverless data infrastructure for epidemiological studies.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  2. Review
  3. A self-updating road map of The Cancer Genome Atlas.Bioinformatics (Oxford, England) · 2013
    Article
  4. Article
  5. Article
  6. Article
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

3 authors.

Jonas S AlmeidaDepartment of Bioinformatics and Computational Biology, The University of Texas M D Anderson Cancer Center, 1515 Holcombe Blvd Houston, TX 77030, USA. jalmeida@mathbiol.org
Helena F Deus
Wolfgang Maass

Funding

U OF TEXAS HLTH SCI CTR HOUSTON CENTER FOR CLINICAL AND TRANSLATIONAL SCIENCESUL1RR024148 · NCRR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2006 to 2010
$27.9M
Integrative Pipeline for Analysis & Translational Application of TCGA Data (GDAC)U24CA143883 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AKBANI, REHAN, MILLS, GORDON B. · 2009 to 2016
$10.6M
NCI NIH HHS 1U24CA143883-01NCRR NIH HHS 1UL1RR024148
6 · The paper itself

Abstract

backgroundBiomedical research is set to greatly benefit from the use of semantic web technologies in the design of computational infrastructure. However, beyond well defined research initiatives, substantial issues of data heterogeneity, source distribution, and privacy currently stand in the way towards the personalization of Medicine.

resultsA computational framework for bioinformatic infrastructure was designed to deal with the heterogeneous data sources and the sensitive mixture of public and private data that characterizes the biomedical domain. This framework consists of a logical model build with semantic web tools, coupled with a Markov process that propagates user operator states. An accompanying open source prototype was developed to meet a series of applications that range from collaborative multi-institution data acquisition efforts to data analysis applications that need to quickly traverse complex data structures. This report describes the two abstractions underlying the S3DB-based infrastructure, logical and numerical, and discusses its generality beyond the immediate confines of existing implementations.

conclusionsThe emergence of the "web as a computer" requires a formal model for the different functionalities involved in reading and writing to it. The S3DB core model proposed was found to address the design criteria of biomedical computational infrastructure, such as those supporting large scale multi-investigator research, clinical trials, and molecular epidemiology.

Indexed as

Models, BiologicalComputational BiologyComputersInternetMarkov Chains

Identifiers

PMID20646315
PMCPMC2918582

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Registered trials

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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.