نتایج جستجو برای: microarray integration

تعداد نتایج: 268861  

Journal: :applied biotechnology reports 0
khadijeh nazari ali karami nezameddin mahdavi amiri fatemeh pourali

dna microarrays consist of collection of dna microscopic spots that in order to form an array attached to a solid surface such as glass, plastic or silicon chip. the pieces of fixed dna considered as a searcher. in this technology it is possible to test sample against thousands probes for specific genes. with this ability, arrays accelerate the biological investigations, gene finding, molecular...

Journal: :Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing 2008
O. Gaevert Steven Van Vooren Bart De Moor

Microarray data are notoriously noisy such that models predicting clinically relevant outcomes often contain many false positive genes. Integration of other data sources can alleviate this problem and enhance gene selection and model building. Probabilistic models provide a natural solution to integrate information by using the prior over model space. We investigated if the use of text informat...

2003
Özgün Babur Emek Demir Aslı Ayaz Uğur Doğrusöz Onur Sakarya

Microarray technology provides cell-scale expression data, however, analyzing this data is notoriously difficult. It is becoming clear that system-oriented methods are needed in order to best interpret this data. Combining microarray expression data with previously built pathway models may provide useful insight about the cellular machinery and reveal mechanisms that govern diseases. Given a qu...

2012
Maurizio Callari Matteo Dugo Valeria Musella Edoardo Marchesi Giovanna Chiorino Maurizia Mello Grand Marco Alessandro Pierotti Maria Grazia Daidone Silvana Canevari Loris De Cecco

BACKGROUND Microarray technology applied to microRNA (miRNA) profiling is a promising tool in many research fields; nevertheless, independent studies characterizing the same pathology have often reported poorly overlapping results. miRNA analysis methods have only recently been systematically compared but only in few cases using clinical samples. METHODOLOGY/PRINCIPAL FINDINGS We investigated...

Journal: :Bioinformatics 2006
Curtis Huttenhower Matthew A. Hibbs Chad L. Myers Olga G. Troyanskaya

MOTIVATION The diverse microarray datasets that have become available over the past several years represent a rich opportunity and challenge for biological data mining. Many supervised and unsupervised methods have been developed for the analysis of individual microarray datasets. However, integrated analysis of multiple datasets can provide a broader insight into genetic regulation of specific...

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