A semantic web approach to biological pathway data reasoning and integration

2006 ◽  
Vol 4 (3) ◽  
pp. 207-215 ◽  
Author(s):  
Kei-Hoi Cheung ◽  
Peishen Qi ◽  
David Tuck ◽  
Michael Krauthammer
Keyword(s):  
Semantic Web ◽  
Biological Pathway ◽  
Pathway Data

A Semantic Web Approach to Biological Pathway Data Reasoning and Integration

2006 ◽  
Author(s):  
Kei-Hoi Cheung ◽  
Peishen Qi ◽  
David Tuck ◽  
Michael Krauthammer
Keyword(s):  
Semantic Web ◽  
Biological Pathway ◽  
Pathway Data

scholarly journals Hierarchical Biological Pathway Data Integration and Mining

10.5772/49974 ◽  
2012 ◽  
Author(s):  
Shubhalaxmi Kher ◽  
Jianling Peng ◽  
Eve Syrkin ◽  
Julie Dickerso
Keyword(s):  
Data Integration ◽  
Biological Pathway ◽  
Pathway Data

scholarly journals Genetic analysis of biological pathway data through genomic randomization

2011 ◽  
Vol 129 (5) ◽  
pp. 563-571 ◽  
Author(s):  
Brian L. Yaspan ◽  
William S. Bush ◽  
Eric S. Torstenson ◽  
Deqiong Ma ◽  
Margaret A. Pericak-Vance ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Biological Pathway ◽  
Pathway Data

scholarly journals Pathway Commons, a web resource for biological pathway data

2010 ◽  
Vol 39 (Database) ◽  
pp. D685-D690 ◽  
Author(s):  
E. G. Cerami ◽  
B. E. Gross ◽  
E. Demir ◽  
I. Rodchenkov ◽  
O. Babur ◽  
...  
Keyword(s):  
Biological Pathway ◽  
Web Resource ◽  
Pathway Data

Pathway Resources at the Rat Genome Database

2011 ◽  
pp. 316-336 ◽  
Author(s):  
Victoria Petri
Keyword(s):  
Research Community ◽  
Biological Pathway ◽  
Genome Database ◽  
Future Directions ◽  
Pathway Information ◽  
Pathway Data ◽  
Pathway Diagrams ◽  
Rat Genome ◽  
Literature Curation

The set of interacting molecules representing a biological pathway or network is a central concept in biology. It is within the pathway context that the functioning of individual molecules acquires purpose and it is the integration of these molecular circuitries that underlies the functioning of biological systems. In order to provide the research community with a dynamic platform for accessing pathway information, the Rat Genome Database (RGD – http://rgd.mcw.edu) is using a multi-tiered approach. In this chapter, the pathway resources that RGD currently offers are presented. Issues covered include: the biological pathway, the concept and the ontology, pathway literature curation and annotation of genes, interactive pathway diagrams, and tools and resources to access and navigate between pathway data. A case study is presented; future directions are discussed.

scholarly journals Semantic Web-Based Integration of Cancer Pathways and Allele Frequency Data

2009 ◽  
Vol 8 ◽  
pp. CIN.S1006 ◽  
Author(s):  
Matthew E. Holford ◽  
Haseena Rajeevan ◽  
Hongyu Zhao ◽  
Kenneth K. Kidd ◽  
Kei-Hoi Cheung
Keyword(s):  
Personalized Medicine ◽  
Semantic Web ◽  
Allele Frequency ◽  
Cancer Drug ◽  
Genome Wide Association Studies ◽  
Frequency Data ◽  
Cancer Pathways ◽  
Ontology Language ◽  
Allele Frequency Data ◽  
Pathway Data

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.

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