کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
946052 | 926173 | 2006 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Utility of Correlation Measures in Analysis of Gene Expression
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
عصب شناسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The role of the correlation structure of gene expression data are two-fold: It is a source of complications and useful information at the same time. Ignoring the strong stochastic dependence between gene expression levels in statistical methodologies for microarray data analysis may deteriorate their performance. However, there is a host of valuable information in the correlation structure that deserves a closer look. A proper use of correlation measures can remedy deficiencies of currently practiced methods that are focused too heavily on strong effects in terms of differential expression of genes. The present paper discusses the utility of correlation measures in microarray data analysis and gene regulatory network reconstruction, along with various pitfalls in both research areas that have been uncovered in methodological studies. These issues have broad applicability to all genomic studies examining the biology, diagnosis, and treatment of neurological disorders.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroRX - Volume 3, Issue 3, July 2006, Pages 384-395
Journal: NeuroRX - Volume 3, Issue 3, July 2006, Pages 384-395
نویسندگان
Anthony Almudevar, Lev B. Klebanov, Xing Qiu, Peter Salzman, Andrei Y. Yakovlev,