Recent advances in modern OMICS technology allow measuring the expression of all kinds of biological entities (genes, proteins, metabolites, miRNAs, etc.) at low cost and in high-throughput. Computational challenges for analyzing such big data emerge, ranging from the low signal to noise ratio to high model complexity, which render simple statistical questions arbitrarily complicated.We will discuss several bioinformatics tools for de-isolating biological networks and multiple OMICS data types: de novo pathway enrichment, in vitro high-throughput screening (HTS) data integration, time-course network enrichment, cancer subtyping, and breath analysis.
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