ISER: selection of differentially expressed genes from DNA array data by non-linear data transformations and local fitting

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ISER: selection of differentially expressed genes from DNA array data by non-linear data transformations and local fitting

SUMMARY This report describes an algorithm (intensity-dependent selection of expression ratios or ISER) developed to analyse DNA array data by optimizing the selection of genes with the most significant variations in expression amongst two RNA samples. The algorithm is designed for use when little or no replication of array hybridizations is available.

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This paper presents adaptive algorithms for ranking and selecting differentially expressed genes from microarray data. A ranking method originally proposed in [1] is adapted and supplemented with Hausdorff distancebased ranking method to improve the performance of the ranking algorithm. A weighted fusion scheme is developed to fuse the ‘mean’ and the Hausdorff distance-based ranking methods to ...

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Microarray data of astrocytes extracted from the optic nerves of donors with and without glaucoma were analyzed to screen for differentially expressed genes (DEGs). Functional exploration with bioinformatic tools was then used to understand the roles of the identified DEGs in glaucoma. Microarray data were downloaded from the Gene Expression Omnibus (GEO) database, which contains 13 astrocyte s...

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Detection of differentially expressed segments in tiling array data

MOTIVATION Tiling arrays have been a mainstay of unbiased genome-wide transcriptomics over the last decade. Currently available approaches to identify expressed or differentially expressed segments in tiling array data are limited in the recovery of the underlying gene structures and require several parameters that are intensity-related or partly dataset-specific. RESULTS We have developed Ti...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2005

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bti729