Abstract: Microarray image processing leads to the characterization of gene expression levels simultaneously, for all cellular transcripts (mRNAs) in a single experiment. The calculation of expression ...
New research from the Data Provenance Initiative has found a dramatic drop in content made available to the collections used to build artificial intelligence. By Kevin Roose Reporting from San ...
One case where OOP has succeeded in R or, at least, is more used than in others is in the Bioconductor Project (bioconductor.org). In Bioconductor we have to deal with complex data structures such as ...
Abstract: In the diagnosis and treatment of cancer, cancer classification is a vital issue. Gene selection is much needed to solve the high dimensionality issue in microarray data, small sample size, ...
The present study was performed to explore the underlying molecular mechanisms and screen hub genes of osteoarthritis (OA) via bioinformatics analysis. In total, twenty-five OA synovial tissue samples ...
A Machine Learning Method to Trace Cancer Primary Lesion Using Microarray-Based Gene Expression Data
Cancer of unknown primary site (CUP) is a heterogeneous group of cancers whose tissue of origin remains unknown after detailed investigation by conventional clinical methods. The number of CUP ...
Microarray gene expression data are analyzed by means of a Bayesian nonparametric model, with emphasis on prediction of future observables, yielding a method for selection of differentially expressed ...
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