John, I am a bit sceptical about the "novel" part of your question. For example the entire study of photosynthesis on thylakoid membranes would fit your description very well, but I doubt it was ever called Mesoscale Biology. In traditional terms, I guess your discipline could equal Cell Biology, Histochemistry and perhaps Molecular and Cell Physiology as something between molecular biology and all the biologies on the other side of the scale. Apparently, there is also a field called Molecular Histology and Cell Biology (see http://en.wikipedia.org/wiki/Histochemistry_and_Cell_Biology). I wonder if it fits your notion of mesoscale biology or not. There is also a C&T Biology department at UCSF, for example (http://ctb.ucsf.edu/). I wonder whether they considered renaming themselves to Integrative Mesoscale Biology in the future :-). Did you have anything in mind that does not fall within any of the fields mentioned?

Matej - you raise several good points. I am imagining that the mesoscale concept would include more integration of multi-scale information in both space and time than is currently being done. Such multi-dimensional integration is more feasible now but I believe that it will demand better ways to combine information rather than simply making huge databases if it is to be transformative. To me, the goal would be a more unified understanding and better predictive biology rather than lots more data per se. Does this make sense?

In other words Cell and Tissue Biology at UCSF seems great in one sense. But the "and" implies these things are being added together and adding is not necessarily integrating. I am asking if we might approach the development of departments that deal with molecules to man by integrating multi-dimensional information across larger temporal and spacial scales than is currently being done. This might involve different types of math and modeling as well as different experimental designs for example. What are your thoughts on these points?

The linking knowledge between how cells organise and function and how the whole organism behaves and interacts with its environment is certainly vast and the middle ground between the two is relatively unexplored. However, I wonder if the idea/aim of 'integrating' across scales is a pragmatic end goal here. Of course scales are relative and whether we are filling in the knowledge gap between the genome and cells or cells and tissues or tissues and the organisim the mesoscale, to my mind, conceptually represents the missing intermediate scale or scales. Whether intermediate scale(s) will enable the linking or integration of disciplines either side or across all scales is a moot point, one that perhaps rests on whether specific scales innately require unique canonical rules of organization and function to account for observations at that length scale. Biology, like the physical sciences, may inherently parcelate into distinct disciplines that only generalize to specific length scales.

So do we primarily strive for integration or do we independently indentify and study novel fields based on a need to understand empirical observations at meso-scale lengths? Or conceptually, do we study the intermediate scales using the language and rules of other length scales (with one eye on integration) or do we de-novo derive new languages with new canonical rules? My fear is that striving for integration is not practical and may indeed be counter-productive. The extended debate then is how we indentify the novel meso-scales in biology? And how new scientific disciplines are borne?

"What are your thoughts on these points?"

I think what you and Andrew discuss now might be the domain of Systems Biology. All the departments that renamed themselves from "Dept of XY" to "Dept of Integrative XY" basically recognized the necessity (or fashion wave?) of applying mathematical models, simulations and systems biology approaches to their disciplines. Among other things, systems approach is concerned with identification of emergent behavior, i.e. one that cannot be ascribed to any of the lower-level components and thus bridging two different levels. Somehow nature "prefers" to be organized in hierarchies with distinct levels which we have to respect whether we like it or not. Often it is not practical or feasible to span more than 2-3 levels. Perhaps not even necessary. To address some of Andrew's concerns: evolution (to work properly) needs the levels to be somewhat independent, otherwise it "could not" change something at one level without ruining the other levels. So I guess we can take it for granted that processes do not influence each other routinely accross many levels.

Your original question now became two separate questions: i) are there levels worth recognizing and studying between macromolecules and tissues? -> macromolecular complexes, organelles, cells? -> studied already by cell biology?.. and ii) how do we study problems at more than 1 level -> modelling and systems biology?

In my view systems biology largely involves defining connections at the systems level. It does not often currently include a bottom up mechanistic understanding. Consequently systems biology is more often correlative than predictive. Biology is more accurately predicted at the molecular level where mechanisms can be defined, i.e. connections depend upon conformations, partners, post-translational-modifications, metabolite ligands, etc. I suggest that mesoscale biology would integrate molecular bottom up with system level top down over time and space so would NOT be systems biology as currently defined.

In thinking about Andrew's answer, I do think there may be a pragmatic end goal to integrating across scales. Consider distinguishing cancer from normal tissue. It is relatively hard to identify a single cell as a cancer cell unless it has obvious chromosome aberrations. Going from cells to tissues ti becomes relatively easy to tell a tumor from normal tissue. In this sense going from genetic changes at the cell level (such as absence of NRCA2) to morphological changes at the tissue level make the problem easier to solve.

John, i currently have doubts regarding the chances for generating a bottom up mechanistic understanding of biological systems. There are some success stories (e.g. modeling of yeast metabolism), but i fear that anything above that level (which hence appears to be at your mesoscale) would currently be within our capabilities. So for a long time to come i beleive we need to be content with descriptive and correlative approaches, which clearly need to be improved (data quality, completeness, compatiblity of different databases, etc...). Having said this i also believe that there will be a need for novel research programs that go beyond the technical issues of omics and systems biology. One particular area might be to study how changes at one level propagate up or down, maybe a bit in the sense of the tumor cell example you have given (However, please not that the phenotypic effect at the tissue level was not derived from a bottom up mechanistic understanding of events at the cell level (e.g. genetic changes) but is based on a correlation)

And i would like to add that i would as much as possible avoid the introduction of new languages with new canonical rules, just look at the abuse of "Systems biology".