The last two projects mentioned in the article (Literome and better interpretation of medical images) sound like they may be useful. The projects that are descr

The last two projects mentioned in the article (Literome and better interpretation of medical images) sound like they may be useful. The projects that are described as cell-debugging and cell-reprogramming sound like the sort of hubristic projects that someone with a good computing background but less than an undergraduate knowledge of cell biology might propose (at least as the projects are described in the article). About a decade ago I was involved with a US Department of Energy effort to model radiation damage to DNA in silico, and more peripherally involved with a proteomics effort working out of the same institution. They didn't work very well. The number one problem was that we didn't have good baseline data from experiments to work with. IMO, you'd get better mileage out of automating in vitro experiments and ensuring that the data is reproducible before you start trying to leverage the latest in computer science. How much can you machine-learn from garbage inputs? Biology experiments even at the isolated cell level are notoriously fiddly. Let the biologists (or at least people who have worked with them) explain the problems that need solving in biology, and then bring in CS people as required. Starting with a computing-oriented perspective is just begging to misunderstand what biological research needs.