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Organization:  Rutgers University New Brunswick

 

Review #2

Proposal Number:

 

0835592

Performing Organization:

 

Rutgers Univ New Brunswick

NSF Program:

 

CDI Type I

Principal Investigator:

 

Rose, Christopher

Proposal Title:

 

CDI Type I:A Communications Theory Approach to Morphogenesis and Architecture Maintenance

Rating:

 

Very Good



REVIEW:

What is the intellectual merit of the proposed activity?

The "big picture" behind this proposal is highly innovative and could lead to major impacts in cell and developmental biology and related areas of medicine. The PIs essentially propose to found a new field and there is a genuine potential for success. The also nicely develop a set of specific scientific questions that this field might address. The topics of tissue morphogenesis, signaling in aging cells, and the possible role of signaling defects in cancers are all important. Furthermore, the proposal sketches out some exciting directions by which they might be pursued.

The major drawback of the proposed work is that it is so ambitious that it must be considered high risk, if high reward. Some of the proposed directions will almost surely lead to completion, e.g., developing capacity/distortion bounds for some forms of cellular communication. Whether these bounds will lead to any meaningful insight into biology is another question, though. The underlying assumption behind the work is that the theoretical bounds will in fact prove limiting on real biological function. If so, there could be a nice payoff in helping us understand why systems have evolved in certain ways or pointing us to other forms of communication we do not yet appreciate. On the other hand, there is a serious risk that the sorts of energy and information theoretic bounds explored here are subsumed by other constraints on cell and tissue behavior. While evolution is a powerful optimization method, it can be extremely difficult to understand its objective function. I would consider there to be a reasonable risk that no real biological insight will flow from this work. Some small practical demonstration projects might go a long way to alleviating that concern, but there is minimal preliminary work described in this proposal.

The proposal is highly responsive to the additional CDI review criteria. The proposed work would be an outstanding example of applying "computational thinking" to a biological problem domain. It lays out a highly innovative way in which computational theory may yield new insights into an important range of biological problems. The proposal is hurt somewhat by the fact that the process seems to be essentially one-way. There does not appear to be any fundamental new information theory likely to emerge from the work, although information theorists would likely be very interested in what it has to say about biology. The proposal is certainly innovative and interdisciplinary, bringing together two investigators with very different backgrounds but a common history of interdisciplinary collaboration. It does have a potential to be paradigm-changing, at least for biology, and to create a substantially new field of exploration. That potential is, however, very speculative.




What are the broader impacts of the proposed activity?

The proposed work has some outstanding potential long-term impacts if it is successful. It could lead to radically new thinking in many fields of biology, as well as major revisions in biology education. These benefits are fairly speculative, however. The shorter-term plan to develop introductory coursework is more concrete and seems a good way to bring benefits to education in the near future. The dissemination plan is very well done and gives high hope that any useful outcomes of the work will be widely accessible.

Summary Statement

The proposal lays out some beautiful ideas for a new approach to using information theory to understand cellular communication and could be paradigm-changing for biology if it succeeds. There would, however, appear to be a high risk that no significant biological results will emerge from it. While it is a great example of applying computational thinking to the biology domain, the feedback to computer science would seem to be fairly limited. There are some nice ideas for incorporating the ideas of the ideas of the proposal into biology education.


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