Linked Life Data

17320499

Source:http://linkedlifedata.com/resource/pubmed/id/17320499

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2007-4-13
pubmed:abstractText
The treatment and management of complex genetic diseases such as osteoporosis can greatly benefit from the integration of relevant research across many different disciplines. We created a text mining tool that analyzes the PubMed literature database and integrates the available genomic information to provide a detailed mapping of the genes and their interrelationships within a particular network such as osteoporosis. The results obtained from our text mining program show that existing genomic data within the PubMed database can effectively be used to predict potentially novel target genes for osteoporosis research that have not previously been reported in the literature. To filter the most significant findings, we developed a ranking system to rate our predicted novel genes. Some of our predicted genes ranked higher than those currently studied, suggesting that they may be of particular interest from a therapeutic standpoint. A preliminary analysis of the current biomedical literature in our research area using our tool suggests that S100A12, as well as a group of SMAD genes previously unstudied in relation to osteoporosis, may be highly relevant to the mechanism of action of bisphosphonates, that the function of osteocytes may be influenced by a family of important interleukins and interleukin-related molecules, and that the FYN oncogene may play an important role in regulating the apoptosis of bone cells in the context of degenerative bone diseases. An evaluation of our tool's predictive ability with an analysis of PubMed literature published before the year 2000 in the area of osteoporosis research shows that many of its top-rated novel target genes from that analysis were later studied and shown to be relevant to osteoporosis in the period between 2000 and 2006. We believe that our tool will be beneficial to researchers in the field of orthopaedics seeking to identify novel target genes in their research area, and it will allow them to delve deeper into the complex interplay between genes, biological systems and diseases.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
8756-3282
pubmed:author
pubmed:issnType
Print
pubmed:volume
40
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1378-88
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
An application of bioinformatics and text mining to the discovery of novel genes related to bone biology.
pubmed:affiliation
Department of Orthopaedic Surgery, UC Davis Medical Center, Orthopaedic Research Laboratory, 4635 2nd Avenue, Room 2000, Sacramento, CA 95817, USA.
pubmed:publicationType
Journal Article