Motivation: Systems biology demands the use of several point of views to get a more comprehensive understanding of biological problems. This usually leads to take into account different data regarding the problem at hand, but it also has to do with using different perspectives of the same data. This multifaceted aspect of systems biology often requires the use of several tools, and it is often hard to get a seamless integration of all of them, which would help the analyst to have an interactive discourse with the data. Results: Focusing on expression profiling, BicOverlapper 2.0 visualizes the most relevant aspects of the analysis, including expression data, profiling analysis results and functional annotation. It also integrates several state-of-the-art numerical methods, such as differential expression analysis, gene set enrichment or biclustering. © 2014 The Author. Published by Oxford University Press. All rights reserved.
CITATION STYLE
Santamaría, R., Therón, R., & Quintales, L. (2014). BicOverlapper 2.0: Visual analysis for gene expression. Bioinformatics, 30(12), 1785–1786. https://doi.org/10.1093/bioinformatics/btu120
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