首页 | 本学科首页   官方微博 | 高级检索  
     


Text-derived concept profiles support assessment of DNA microarray data for acute myeloid leukemia and for androgen receptor stimulation
Authors:Rob Jelier  Guido Jenster  Lambert CJ Dorssers  Bas J Wouters  Peter JM Hendriksen  Barend Mons  Ruud Delwel  Jan A Kors
Affiliation:(1) Department of Medical Informatics, Erasmus MC – University Medical Center, Rotterdam, The Netherlands;(2) Department of Urology, Erasmus MC – University Medical Center, Rotterdam, The Netherlands;(3) Department of Pathology, Erasmus MC – University Medical Center, Rotterdam, The Netherlands;(4) Department of Hematology, Erasmus MC – University Medical Center, Rotterdam, The Netherlands
Abstract:

Background  

High-throughput experiments, such as with DNA microarrays, typically result in hundreds of genes potentially relevant to the process under study, rendering the interpretation of these experiments problematic. Here, we propose and evaluate an approach to find functional associations between large numbers of genes and other biomedical concepts from free-text literature. For each gene, a profile of related concepts is constructed that summarizes the context in which the gene is mentioned in literature. We assign a weight to each concept in the profile based on a likelihood ratio measure. Gene concept profiles can then be clustered to find related genes and other concepts.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号