Evidence map›Paper›PMID 19458791›Full record

ArticleCancer informatics2009

Semantic Web-based integration of cancer pathways and allele frequency data.

Matthew E Holford, Haseena Rajeevan, Hongyu Zhao, Kenneth K Kidd, Kei-Hoi Cheung

Abstract read
In one paragraph

Article in Cancer informatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Semantic-Web Architecture for Electronic Discharge Summary Based on OWL 2.0 Standard.Acta informatica medica : AIM : journal of the Society for Medical Informatics of Bosnia & Herzegovina : casopis Drustva za medicinsku informatiku BiH · 2016
    Article
  2. 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

5 authors.

Matthew E HolfordDepartment of Biostatistics, School of Public Health, Yale University, New Haven, CT, USA.
Haseena Rajeevan
Hongyu Zhao
Kenneth K Kidd
Kei-Hoi Cheung

Funding

MEDICAL INFORMATICS RESEARCH TRAINING AT YALET15LM007056 · NLM · YALE UNIVERSITY · PI Mark Bender Gerstein, LUCILA OHNO-MACHADO · 1987 to 2026
$22.2M
SENSELAB: INTEGRATION OF MULTIDISCIPLINARY SENSORY DATAP01DC004732 · NIDCD · YALE UNIVERSITY · PI SHEPHERD, GORDON · 2000 to 2008
$10.2M
Yale Microarray Center for Research the Nervous SystemU24NS051869 · NINDS · YALE UNIVERSITY · PI MANE, SHRIKANT M · 2005 to 2009
$6.9M
STATISTICAL METHODS TO MAP GENES FOR COMPLEX TRAITSR01GM059507 · NIGMS · YALE UNIVERSITY · PI ZHAO, HONGYU · 1999 to 2013
$3.6M
NIDCD NIH HHS P01 DC004732NIGMS NIH HHS R01 GM059507NINDS NIH HHS U24 NS051869NLM NIH HHS T15 LM007056
6 · The paper itself

Abstract

We demonstrate the use of Semantic Web technology to integrate the ALFRED allele frequency database and the Starpath pathway resource. The linking of population-specific genotype data with cancer-related pathway data is potentially useful given the growing interest in personalized medicine and the exploitation of pathway knowledge for cancer drug discovery. We model our data using the Web Ontology Language (OWL), drawing upon ideas from existing standard formats BioPAX for pathway data and PML for allele frequency data. We store our data within an Oracle database, using Oracle Semantic Technologies. We then query the data using Oracle's rule-based inference engine and SPARQL-like RDF query language. The ability to perform queries across the domains of population genetics and pathways offers the potential to answer a number of cancer-related research questions. Among the possibilities is the ability to identify genetic variants which are associated with cancer pathways and whose frequency varies significantly between ethnic groups. This sort of information could be useful for designing clinical studies and for providing background data in personalized medicine. It could also assist with the interpretation of genetic analysis results such as those from genome-wide association studies.

Identifiers

PMID19458791
PMCPMC2664696

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.