DocumentCode :
1623829
Title :
Finding the right genes for disease and prognosis prediction
Author :
Hall, Lawrence O.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
fYear :
2010
Firstpage :
1
Lastpage :
2
Abstract :
It is possible to get gene expression data relatively inexpensively from micro-arrays. So, this leads to hope that the genes can tell us who will get or has a disease. Perhaps one can find the stage of the disease to enable effective treatments. However, we are currently at the stage where there are many challenges to evaluating the possibilities for genes to be used in diagnosis and treatment. There are typically many more genes that might be involved than samples for any given disease. Which genes are important and how stable are the choices an algorithm provides? We do not know the time of the true onset of a disease, just sometimes when symptoms started and sometimes when diagnosis was done. Some of the promising work on diagnosis or prognosis has suffered from data or scientific errors. This talk will discuss the problems and pitfalls of using genes to predict disease presence or prognosis. It will also discuss some promising ways to choose the genes that may be predictive for a particular disease, with a focus on cancer, and point out some open questions.
Keywords :
biology computing; diseases; genetics; medical diagnostic computing; disease prediction; gene expression data; prognosis prediction; Artificial intelligence; Awards activities; Computer science; Conferences; Data mining; Diseases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Science and Engineering (ICSSE), 2010 International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-6472-2
Type :
conf
DOI :
10.1109/ICSSE.2010.5551766
Filename :
5551766
Link To Document :
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