CrossNorm: a novel normalization strategy for microarray data in cancers.
Y.N. analyzed microarray data in the initial stage of this work, and N.H. and E.S. accomplished microarray data analyses.
All microarray data in the present study were obtained in accordance with the Minimum Information About a Microarray Experiment (MIAME) guidelines.
In this study, chemometric strategies were applied to microarray data in order to develop an appropriate normalisation method.
Using chromatin immunoprecipitation (ChIP) sequencing and microarray data, in silico analyses were conducted to identify and characterize unique and overlapping GLI1 and GLI2 binding regions in neoplastic chondrocytes.
In this study, we used SplicerEX to compare conventional and exon-based Affymetrix microarray data in a model of EBV transformation of primary human B cells.
Advancements in measurement techniques and computing methodologies have resulted in the use of microarray data in application to genetics, medicine, and patient diagnosis.
MAMA was applied to the microarray data in rice subjected to Fe deficiency, and the accumulation of motif pairs was also evaluated using this method.
Based on the collection of the most comprehensive microarray data in ROAD (Table 2), we also developed co-expression analysis tools in ROAD.
The microarray data in the.
The clustering method is different from all existing clustering approaches for microarray data in the literature.
