Evidence map›Paper›PMID 23188758›Full record

ReviewWiley interdisciplinary reviews. Systems biology and medicine

Accelerating cancer systems biology research through Semantic Web technology.

Zhihui Wang, Jonathan Sagotsky, Thomas Taylor, Patrick Shironoshita, Thomas S Deisboeck

Abstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. Systems biology and medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Integrated PK-PD and agent-based modeling in oncology.Journal of pharmacokinetics and pharmacodynamics · 2015
    Review
  4. Article
  5. Review
  6. Article
  7. Review
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

5 authors.

Zhihui WangDepartment of Pathology, University of New Mexico, Albuquerque, NM, USA.
Jonathan Sagotsky
Thomas Taylor
Patrick Shironoshita
Thomas S Deisboeck

Funding

Subproject OneU56CA113004 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DEISBOECK, THOMAS S · 2004 to 2009
$3.4M
NCI NIH HHS CA 113004NCI NIH HHS U56 CA113004
6 · The paper itself

Abstract

Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web-based collaborative cancer research by presenting data in a manner that is self-descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter-organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute's caBIG, so users can interact with the DMR not only through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter-institutional collaboration on cancer modeling projects, online grid-based execution of shared models, and the collaboration workflow protecting researchers' intellectual property.

Indexed as

Database Management SystemsInternetNeoplasmsComputer GraphicsDatabases, FactualHumansSemanticsSystems BiologyUser-Computer Interface

Identifiers

PMID23188758
PMCPMC3558557

What OpenQuestion holds

Textmetadata
LicenceTDM
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.