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Be The Cell

“On its path from a fertilized egg to one of the many cell types in a multicellular organism, a cell turns the blank canvas of its early embryonic state into a molecular profile finetuned to achieve a vital organismal function.

This remarkable transformation emerges from the interplay between dynamically changing external signals, the cell’s internal, variable state, and tremendously complex molecular machinery; we are only beginning to understand.” [1]

In as much as formal mathematics and artificial intelligence methods like machine learning are man made concepts borne of the so-called hard sciences, e.g. – physics, chemistry, geology etc., they can never fully capture the essence of biological, emergent development.

It is simply because of the precise lack of specificity as to its fate inherent in every cell upon its inception, that defies adequate description by these otherwise formidable tools used throughout other branches of science and natural phenomena.

Living cells are very well enabled in their beginning, but their ultimate fate is never specified. That arises only after an almost happenstance journey through an equally unspecified environment and its feedback onto the cell’s internal biological mechanisms, as it develops; and, in return, the cell’s own resulting impact on its environment, and so on.

Each step along a cell’s developmental journey is literally enabled by its previous step’s developmental processes and outcomes. Such a chain reaction defined by prior step dependencies can never be precisely specified.

If we are to even attempt an accurate grasp of such a beautifully delicate, yet stochastic waltz in nature, we are compelled to think and act as a living cell; step by step, reflecting each new step’s capabilities, and resulting impact on its environment.

In other words, we must immerse our understanding and analytical abilities within the cell’s world and its environment; we have to “Be The Cell”. #BeTheCell

[1] Maria Mircea, Stefan Semrau; How a cell decides its own fate: a single-cell view of molecular
mechanisms and dynamics of cell-type specification. Biochem Soc Trans 17 December 2021; 49
(6): 2509–2525. doi:

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