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Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity
المؤلفون المشاركون
Eschrich, Steven A.
Kamath, Vidya P.
Torres-Roca, Javier F.
المصدر
International Journal of Genomics
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-02-08
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
The use of gene expression-based classifiers has resulted in a number of promising potential signatures of patient diagnosis, prognosis, and response to therapy.
However, these approaches have also created difficulties in trying to use gene expression alone to predict a complex trait.
A practical approach to this problem is to integrate existing biological knowledge with gene expression to build a composite predictor.
We studied the problem of predicting radiation sensitivity within human cancer cell lines from gene expression.
First, we present evidence for the need to integrate known biological conditions (tissue of origin, RAS, and p53 mutational status) into a gene expression prediction problem involving radiation sensitivity.
Next, we demonstrate using linear regression, a technique for incorporating this knowledge.
The resulting correlations between gene expression and radiation sensitivity improved through the use of this technique (best-fit adjusted R2 increased from 0.3 to 0.84).
Overfitting of data was examined through the use of simulation.
The results reinforce the concept that radiation sensitivity is not driven solely by gene expression, but rather by a combination of distinct parameters.
We show that accounting for biological heterogeneity significantly improves the ability of the model to identify genes that are associated with radiosensitivity.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Kamath, Vidya P.& Torres-Roca, Javier F.& Eschrich, Steven A.. 2017. Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity. International Journal of Genomics،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1167187
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Kamath, Vidya P.…[et al.]. Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity. International Journal of Genomics No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1167187
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Kamath, Vidya P.& Torres-Roca, Javier F.& Eschrich, Steven A.. Integrating Biological Covariates into Gene Expression-Based Predictors of Radiation Sensitivity. International Journal of Genomics. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1167187
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1167187
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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