Two recent studies yet again point to the principle that in an evolving living universe we can never come to the end of knowledge about it. However, by plumbing what we don't yet know, we can outline where areas of advancement in knowledge most probably lie.
In a remarkable survey of the protein communities, it has been estimated that we probably know less than half of what makes up cellular organization. This was made possible by combining two technologies via artificial intelligence as the article makes clear. (This use of AI as a method of categorizing biological functions does not mean that it replaces human creative thinking but merely aids it.)
The second study used the very same database MuSIC 1.0 or multi-scale integrated cell to show how families of proteins are organized as subunits of interactions. Again, the tool of AI is used to measure the distance of protein functions.
In addition, yet another study from Baylor School of Medicine and the Czech Academy of Sciences shows remarkable evidence of the coordination of protein complexes regulating transcription in an astoundingly harmonic orchestral fashion. This discovery of such wonderfully precise and delicate fine tuning at the cellular level yet again harkens back to Leibniz' dictum of pre-established harmony.
In this blog, I have attempted to show how a method adopted from Riemannian geometry fits the protein "interactome." The machinery of protein aggregates operates across a multiply connected manifold of functions. Individual and groups of proteins also may play roles as singularities that operate in separate and distinct functions. In this way, the Riemann surface function adequately models the global connections of these individual and protein conglomerates.
At the higher level of such global organization in virtually all realms of physics, biophysics and human psychology Riemann's principle of geometrical mapping of multidimensional interrelationships holds enduring value. And no doubt will be applied to successfully to organize such databases.