Pathway activity hallmarks development – not a gene expression experiment

The relationship between cells is driven by how you tell them apart

Understanding development arising from stem cells using molecular profiles like gene expression microarray, genome wide methylation marks, RNASeq, and histone mark dynamics is currently our state of the art. All of these approaches measure a single dimension of molecular event. How can this be translated to how the cell is functioning at the developmental time point, and how can this be compared between experiments that are using different platforms, cell types, and whatever else?

We need to figure out what the overall functional state of the cell is at the developmental snapshot we are taking. If we can do that then its possible to compare functional states – which are made up of the sum of the assay activities we are performing already, and draw the conclusions accordingly.

If we know the individual processes that are working together (ooops, I nearly said Systems Biology), then we can assess what processes, made up of signaling pathways for instance, are driving cell development.

There have been a number of papers (1. 2. 3. ) lately heading in this direction – its important as we need to think beyond the gene and the SNP. They simply don’t work in isolation.


About winhide

I develop and use computational biology approaches to impact global public health in research such as understanding of stem cell biology, systematics of cellular profiling and complex diseases.
This entry was posted in bioinformatics, Data sharing, genome data sharing, Genomics, networks, pathways, Stem Cell, stem cell bioinformatics, Uncategorized and tagged , , , , , , , , , , , . Bookmark the permalink.

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