The first (and perhaps the most important one) is the fact that D2OL and other DC paradigms do not offer something extremely novel to write a paper about. Don't get me wrong, I am not saying that there is nothing to DC, but it is a utility, an infrastructure issue. As such, when a DC based project publishes something, it will (normally) be in a computing journal, normally under the Distributed, Parallel, Cluster and lately Grid computation areas. IEEE Xplore and ACM procedings are good examples (google them), where a composite search with the aformentioned keywords will give you hits. The algorithm that the DC utility runs is another story and this is where the important publishing results (as far as the life science is concerned) are located. D2OL for instance, goes by the keyword of 'ligand docking', a general field of protein docking and molecular modeling, with links to structural bioinformatics, the subfield of bioinformatics that has to do with protein function. Good examples of journals where you can search for the latest advances in the field are: http://bioinformatics.oxfordjournals.org/ and use keyword searches such as 'ligand docking'. This is the stuff that makes publications and allows scientists to target ligands to proteins in silico, identify candidates and then replicate only the promising results in the labs to make drugs such as tamiflu and others. Consequently, when a scientist publishes something in the life science field, the effort goes into explaining the algorithm in detail, rather than the infrastructure. In the same way, most papers about climate modeling focus on the model itself, rather than the computing paradigm. The whole idea about a DC based grid is afterall to act as a utility, a platform to run your algorithm on and get your results.